Autonomous digital media processing systems and methods

ABSTRACT

A system for monitoring and recording and processing an activity includes one or more cameras for automatically recording video of the activity. A remote media system is located at the location of the activity. A network media processor and services is communicatively coupled with the remote media system. The remote media system includes one or more AI enabled cameras. The AI enabled camera is configured to record the activity. The network media processor is configured to receive an activation request of the AI enabled camera and the validate the record request.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.17/339,771, entitled “Autonomous Digital Media Processing Systems andMethods” filed Jun. 4, 2021, which claims the benefit of U.S.Provisional Patent Application No. 63/034,667, entitled “AutonomousActivity Monitoring and Lottery System and Method” filed Jun. 4, 2020,the entire content of which is hereby incorporated by reference in itsentirety.

FIELD OF THE INVENTION

The present disclosure is directed to digital media production. Moreparticularly, the present disclosure is directed to autonomous digitalmedia processing systems and methods.

BACKGROUND OF THE INVENTION

Various forms of video recording and production exist in today. Forexample, motion picture video production is a very labor intense effort,with a director taking multiple shots from multiple view angles, andpost production taking months to produce a final video. Such videorecording is very expensive and requires a large amount of humanresources. In sports, video streaming technology is used to capturereal-life events, and does so with cameramen and women moving cameras inthe direction of where the play is occurring. This can allow for areal-time recording with camera cuts being made to different aspects ofplay. Although the length of time is very compressed, there still existsa need to manually record and follow the field of play to capture thedesired footage. In another aspect, for live sports video, the video isstreamed in near real-time using a dedicated, high speed networkconfigured to broadcast televised sporting events. However, what each ofthese systems is lacking an automatic means to process and communicatevideo footage without the need of having a director or videographercapture relevant footage, and an automated way to produce andcommunicate video to viewers in an efficient manner.

SUMMARY

It is an aspect of the disclosure to provide a system for automaticallyrecording an athletic event.

In one aspect, a system for autonomously providing digital media isprovided, comprising: a remote media system (RMS) located at a golfcourse having a golf hole, wherein the RMS includes: a first AI enabledcamera configured to record a video of a golfer detected at the golfhole; and a communication interface configured to receive an input toactivate a video recording of the golfer at the golf hole, wherein thevideo recording includes a plurality of images of the golfer havingobjects within the images that are detectable using an AI logic; anetwork media processor and services (NMS) communicatively coupled tothe RMS and located remote to the RMS, the NMS including: a networkcommunication interface configured to initiate a record event requestincluding the input to activate the video recording, the record eventrequest communicated to the RMS; and a network media processorconfigured to receive an activation request of the AI enabled camera andto validate the record request; and a digital media enabled destinationincluding a mobile application configured to send the session request tothe NMS to activate the video recording, wherein the request includes aunique identifier of the digital media enabled destination, a locationof the golf hole, and a user profile identifier.

In another aspect, a method for autonomously providing digital media isprovided, comprising: detecting a presence of a golfer at a golf hole ona golf course; receiving an activation request in response to thedetected presence, the activation request including a user profileidentifier of the golfer; validating the golfer using the user profileidentifier and the location of the golf hole; sending an activationrequest and activating a recording of the golfer using an AI enabledcamera at the golf hole upon the golfer being valid; and not activatingthe recording upon the golfer not being valid.

In another aspect, an AI enabled golf course is provided, comprising: afirst golf hole having a green, a tee box, and a hole with a flagstickpositioned within the hole; and an AI enabled camera positioned near thetee box and configured to automatically record a golfer present on thegolf hole, wherein the recording is in response to detecting the golfernear the tee box.

In another aspect, an AI enabled golf course is provided, comprising: afirst golf hole having a green, a tee box, and a hole with a flagstickpositioned within the hole; and a remote media system (RMS) located atthe golf course having a golf hole, wherein the RMS includes: a first AIenabled camera configured to record a video of a golfer detected at thegolf hole, wherein the first AI enable camera is located in a fixed andpermanent location at the golf hole; and a communication interfaceconfigured to receive an input to activate a video recording of thegolfer at the golf hole, wherein the video recording includes aplurality of images of the golfer having objects within the images thatare detectable using an AI logic; wherein the input to activate thevideo recording is received from a network media processor and services(NMS) communicatively coupled to the RMS and located remote to the RMS,the NMS including: a network communication interface configured toinitiate a record event request including the input to activate thevideo recording, the record event request communicated to the RMS; and anetwork media processor configured to receive an activation request ofthe AI enabled camera and to validate the record request; and whereinthe NMS is in communication with a digital media enabled destinationincluding a mobile application configured to send the session request tothe NMS to activate the video recording, wherein the request includes aunique identifier of the digital media enabled destination, a locationof the golf hole, and a user profile identifier.

BRIEF DESCRIPTION OF THE DRAWINGS

Other aspects of the present disclosure will be readily appreciated, asthe same becomes better understood by reference to the followingdetailed description when considered in connection with the accompanyingdrawings wherein:

FIG. 1 is a diagram illustrating an autonomous media processing systemin accordance with an aspect of the present disclosure;

FIG. 2 is a block diagram illustrating a remote media capture system inaccordance with an aspect of the present disclosure;

FIG. 3 is a block diagram illustrating an AI enabled camera for use witha remote media capture system in accordance with an aspect of thepresent disclosure;

FIG. 4 is a block diagram illustrating network media processing andmanagement services in accordance with an aspect of the presentdisclosure;

FIGS. 5A-D are graphical user interfaces of a media enabled mobileapplication according to an aspect of the present disclosure;

FIG. 6 is a diagram of an AI enabled golf course according to an aspectof the present disclosure;

FIG. 7 is a block diagram illustrating an AI enabled golf hole accordingto an aspect of the present disclosure;

FIG. 8 illustrates a method of activating recording using an autonomousmedia processing system according to an aspect of the presentdisclosure;

FIG. 9 illustrates a method of autonomous media post processingaccording to an aspect of the present disclosure;

FIG. 10 illustrates a method of using a media enabled mobile applicationaccording to an aspect of the present disclosure; and

FIG. 11 illustrates a block diagram illustrating a multi-view AI enabledgolf hole according to an aspect of the present disclosure.

DETAILED DESCRIPTION OF THE DISCLOSURE

The following description in combination with the Figures is provided toassist in understanding the teachings disclosed herein. The followingdiscussion will focus on specific implementations and embodiments of theteachings. This focus is provided to assist in describing the teachingsand should not be interpreted as a limitation on the scope orapplicability of the teachings. However, other teachings can certainlybe utilized in this application. The teachings can also be utilized inother applications and with several different types of architecturessuch as distributed computing architectures, client/serverarchitectures, or middleware server architectures and associatedcomponents.

Devices or programs that are in communication with one another need notbe in continuous communication with each other unless expresslyspecified otherwise. In addition, devices or programs that are incommunication with one another may communicate directly or indirectlythrough one or more intermediaries.

Embodiments discussed below describe, in part, distributed computingsolutions that manage all or part of a communicative interaction betweennetwork elements. In this context, a communicative interaction mayinclude sending information, requesting information, receivinginformation, receiving a request for information, or any combinationthereof. As such, a communicative interaction could be unidirectional,bidirectional, multi-directional, or any combination thereof. In somecircumstances, a communicative interaction could be relatively complexand involve two or more network elements. For example, a communicativeinteraction may be “a conversation” or series of related communicationsbetween a client and a server—each network element sending and receivinginformation to and from the other. The communicative interaction betweenthe network elements is not necessarily limited to only one specificform. A network element may be a node, a piece of hardware, software,firmware, middleware, another component of a computing system, or anycombination thereof.

In the description below, a flow-charted technique or algorithm may bedescribed in a series of sequential actions. Unless expressly stated tothe contrary, the sequence of the actions and the party performing theactions may be freely changed without departing from the scope of theteachings. Actions may be added, deleted, or altered in several ways.Similarly, the actions may be re-ordered or looped. Further, althoughprocesses, methods, algorithms or the like may be described in asequential order, such processes, methods, algorithms, or anycombination thereof may be operable to be performed in alternativeorders. Further, some actions within a process, method, or algorithm maybe performed simultaneously during at least a point in time (e.g.,actions performed in parallel), can also be performed in whole, in part,or any combination thereof. As used herein, the terms “comprises,”“comprising,” “includes,” “including,” “has,” “having” or any othervariation thereof, are intended to cover a non-exclusive inclusion. Forexample, a process, method, article, or apparatus that comprises a listof features is not necessarily limited only to those features but mayinclude other features not expressly listed or inherent to such process,method, article, or apparatus. Further, unless expressly stated to thecontrary, “or” refers to an inclusive-or and not to an exclusive-or. Forexample, a condition A or B is satisfied by any one of the following: Ais true (or present) and B is false (or not present), A is false (or notpresent) and B is true (or present), and both A and B are true (orpresent).

Also, the use of “a” or “an” is employed to describe elements andcomponents described herein. This is done merely for convenience and togive a general sense of the scope of the invention. This descriptionshould be read to include one or at least one and the singular alsoincludes the plural, or vice versa, unless it is clear that it is meantotherwise. For example, when a single device is described herein, morethan one device may be used in place of a single device. Similarly,where more than one device is described herein, a single device may besubstituted for that one device.

Unless otherwise defined, all technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art to which this invention belongs. Although methods and materialssimilar or equivalent to those described herein can be used in thepractice or testing of embodiments of the present invention, suitablemethods and materials are described below. All publications, patentapplications, patents, and other references mentioned herein areincorporated by reference in their entirety, unless a particular passageis cited. In case of conflict, the present specification, includingdefinitions, will control. In addition, the materials, methods, andexamples are illustrative only and not intended to be limiting.

To the extent not described herein, many details regarding specificmaterials, processing acts, and circuits are conventional and may befound in textbooks and other sources within the computing, electronics,and software arts.

For purposes of this disclosure, media processing system and servicescan include any instrumentality or aggregate of instrumentalitiesoperable to compute, classify, process, transmit, receive, retrieve,originate, switch, store, display, manifest, detect, record, reproduce,handle, or utilize any form of information, intelligence, or data forbusiness, scientific, control, entertainment, or other purposes. Forexample, a media processing system can be a mobile device, a digitalcamera, a personal computer, a PDA, a consumer electronic device, asmart phone, a set-top box, a digital media subscriber module, one ormore cloud or network services and storage, a cable modem, a fiber opticenabled communications device, a media gateway, a network server orstorage device, a switch router, wireless router, or other networkcommunication device, or any other suitable device and can vary in size,shape, performance, functionality, and price.

Processors disclosed herein can include memory, one or more processingresources or controllers such as a central processing unit (CPU),hardware, local memory or software control logic. Additional componentscan include one or more memory devices including internal and externalstorage devices, one or more wireless, wired communications interfaces,a display, an input device such as a keypad, touchscreen, touchpad,voice recognition, face or AI enabled image recognition, one or morecameras or camera inputs, audio inputs, power supplies, or variouscombinations. Processors can be embedded within a media processingsystem, can be provided separate from a media processing system, or incombination thereof. Processors can also be realized as digital logiconly stored within a service such as an API, network services such asAmazon Cloud service, or combinations thereof. Other forms of processorsare described herein as examples that can be deployed within the scopeof the present disclosure.

Various software aspects that can be used within the media processingsystem may include Linux operating system having Python programmedapplications, OpenCV image processing library, AWS Greengrass ML ModelDevelopment and Execution, video editing software using OpenCV imageprocessing library and Python programming. Various cloud services andfor storing, sending, and accessing video may be used, including AWS S3and AWS Glacier for video storage, and AWS CloudFront for contentdelivery and distribution. Cloud services for processing and editingvideo may include Python and OpenCV running on AWS EC2 servers. Cloudservices for converting videos from one format to another may includeAWS Elemental MediaConvert.

Embodiments of autonomous media processing systems and processorsdisclosed herein also use Artificial Intelligence (AI) or AI Logic,Machine Learning, and Neural Networks generally described as AI Logic.AI or AI Logic includes a several categories of techniques that allowsystems and processors to mimic human capabilities. AI techniques orlogic include Machine Learning, Speech and Language Processing, ExpertSystems, and Robotics. Machine Learning is the subset of AI that enablescomputers to improve at tasks through experience. Machine Learningincludes traditional statistics-based approaches such as RegressionAnalysis and newer techniques like Deep Learning. Deep Learning useslarge amounts of historical data to train multilevel Neural Networks todraw conclusions about new data. Throughout the specification, thedescription also uses AI logic that deploys Deep Learning, in the formof Neural Networks, to identify classes of objects, object locations invideo images and segments. Deep Learning is also used to identifydistinctive activities or sub-activities within video images and videosegments including multiple video frames. In some forms,Statistics-based machine learning is used to characterize the motion ordirection of objects within the video images and segments.

AI or AI logic disclosed herein can also include cloud services forgenerating a Neural Network to create AI logic and AI gesturerecognition logic and can include AWS SageMaker for constructing,training, tuning, and evaluating machine learning models, including butnot limited to Keras/TensorFlow developmental framework, and SagemakerNEO to prepare models for deployment to one or more AI logic locations.

Various embodiments of autonomous media processing systems and methodswill now be more fully described. Each of these example aspects areprovided so that this disclosure is thorough and fully conveys the scopeof the inventive concepts, features and advantages to those skilled inthe art. To this end, numerous specific details are set forth such asexamples of specific components and methods associated with the systemto provide a thorough understanding of each of the aspects associatedwith the present disclosure. However, as will be apparent to thoseskilled in the art, not all specific details described herein need to beemployed, the example aspects may be embodied in many different forms,and thus should not be construed or interpreted to limit the scope ofthe disclosure.

Various embodiments disclose the capture, process, distribution and useof video, audio, and content used to create media or digital media. Theembodiments disclosed herein include autonomous and AI enabled systems,devices, methods, applications, software, hardware, and locations forcapturing, processing, distributing and consuming digital media. Asdisclosed herein, digital media can mean any media that are encoded inmachine-readable formats. Digital media can be created, viewed,distributed, modified, listened, and preserved on a digital electronicdevice. Digital media refers to any information that is broadcastthrough a screen or speakers and can include text, audio, video, andgraphics that are transmitted over the Internet or digital communicationmediums. Examples of digital media include software, digital images,digital video, video games, web pages and websites, social media,digital data and databases, digital audio such as MP3, electronicdocuments and electronic books. As disclosed herein, media and digitalmedia are used throughout the specification and unless expresslyspecified as being different they should be referred to as describedabove.

Referring now to FIG. 1 , an autonomous media processing system isdisclosed. Autonomous Media Processing System (AMPS), generallyillustrated at 100, includes a Remote Media System (RMS) 102, a networkmedia processing and management services (NMS) 104, and a media enableddestination 106. AMPS 100 further includes AI logic 108 which caninclude remote AI logic 110 accessible to RMS 102. AI logic 108 alsoinclude network AI logic 112 accessible to NMS 104. Portions or all ofAI logic 108 can be stored at either or both of remote AI logic 110 ornetwork AI logic 112.

According to an aspect, AI logic 108 can include a learned logicgenerated based on previous recordings of image data that can be used togenerate an AI logic specific to the field of use being deployed. By wayof example, AMPS 100 can be used with one or more golf courses and AIlogic can be created to generate AI golf logic as AI logic 108. As such,AI golf logic can be inclusive of AI logic with elements of AI logicdesigned to be used for golf. For example, AI golf logic can includeobjects that can be used to identify specific players, clothing,equipment, other items associated with a golf course or its environment.For example, AI golf logic can include a human, a human or golferholding a golf club, a shirt, a shirt color, a hat, a hat color, a golfglove, golf shoes, a golf cart, persons in a golf cart, a golf ball, agolf tee, a golf club, an iron, a driver, a utility club, a putter, awedge, a 1-iron, a 2-iron, a 3-iron, a 4-iron, a 5-iron, a 6-iron, a7-iron, an 8-iron, a 9-iron, a wedge, a pitching wedge, a gap wedge, asand wedge, a golf ball logo, a male, a female, a child, a junior, aleft handed golfer, a right golfer, a shirt logo, caddies, a marshal,equipment brands such as Callaway, Taylor-Made, Titleist, Mizuno, andothers. Various other objects can be identified within AI logic 108 asneeded or required.

According to another aspect, AI logic 108 can include objects used at agolf course, golf hole and surrounding environments. For example, AIlogic 108 can include logic for identifying tee boxes, a color of a teebox, a golf cart, trees, a fairway, a cart path, a green, a hole, a pin,a sand bunker, a water hazard, a grass hazard, out-of-bounds, a rough, afirst cut of a green, a second cut of a green, birds, insects, animals,distance from a tee to a pin, distance from a tee to a front of a green,distance from a tee to middle of a green, distance from a tee to a backof a green, red stakes, white stakes, blue stakes, yellow stakes, redlines, white lines, yellow lines, changes in elevation, clouds, rain,snow, fog, mist, mud, wind, topology of the green, cut of the hole, amaintenance crew member, a lawn mower, leaf blower, a rake, a sand rake,or various other objects that can be identified and added and used by AIlogic 108 for use to process video or images captured at a golf course.

In addition to object identification, AI logic 108 can also beconfigured to identify gestures created within video. Gesture logic, orgesture recognition, can be identified using AI logic 108 by processinga series of image frames and comparing the image frames to AI logic 108having gesture logic. Although gesture logic is described as AI logic108, one can appreciate that gesture logic can be provided alone or incombination with other objects within AI logic 108. Examples of gesturelogic are not limited to golf gestures and can include various imageframes defined as gestures. For example, gesture logic for golf caninclude pre-shot gesture routines, shot or swing gestures, and post-shotgestures.

According to an aspect, swing gestures can include identifying a golferon a tee box, a practice swing, a golfer talking to other golfers, agolfer looking at a distance to a pin, a golfer setting a ball on a balltee, a golfer stepping behind a ball, a golfer aligning for a swing, agolfer addressing a ball, a golf cart pulling up, a golfer walking up, agolfer carrying a bag, a golfer pushing bag on a cart, a golfer pullingbag on a cart, a golfer walking with caddie, a golfer reviewing a scorecard, or various other pre-shot gestures that can be learned and addedto AI logic 108.

Additional gesture logic that can be included within AI logic 108 caninclude gestures related to a golfer's shot, including but not limitedto, a backswing, a downswing, contact with a ball, missing a ball,duffing a ball, topping a ball, fatting a ball, thinning a ball,shanking a ball, hooking a ball, slicing a ball, popping a ball up,pulling a ball, pushing a ball, hitting a ball straight, hitting a balllow, hitting a ball high, a ball landing on a green, a ball landing insand, a ball landing in water, a ball landing in rough, a ball landingout-of-bounds, a ball hit into trees, a ball hitting a tree, a ballhitting a pin, a ball hitting a cart path, a ball hitting agolfer/person, putting, putting too hard, putting too soft, puttingleft, putting right, hitting a ball past a green, hitting a ball shortof a green, hitting a ball left of a green, hitting a ball right of agreen, or various other shot gestures that can be learned and added toAI logic 108.

According to a further aspect, AI logic 108 can also include golf logichaving post-shot gestures that can be identified. Post-shot gestures,can include, but are not limited to slamming a club, throwing a club,golfer giving a high five, golfer giving a first bump, golfer puttinghis arms in the air, golfer pumping his fist, golfer running, golferjumping, golfer slouching, golfer yelling, golfer picking up a tee,golfer walking straight ahead, golfer clapping, golfer laughing, orvarious other post-shot gestures that can be learned and added to AIlogic 108.

According to a further aspect, AI logic 108 having object and gesturerecognition can be used to identify kinematic aspects of a golfer'sswing. Using AI logic 108, object recognition logic and gesturerecognition logic can be used to identify a type of golf swing a golfermay have made while hitting a golf ball. For example, AI logic 108objects can be used to identify a golf club, arms, legs, hips, a golfclub, a tee box, or other objects associated with a golfer. AI logic 108gesture logic can be used with object logic to identify the path of theclub, movement of arms, legs, hips, wrist, golf club, golf ball, launchangle of ball, velocity of a ball, smash factor of a ball, side spin ofa ball, apex of a struck ball, and various other gesture activities of agolfer, club, and ball. A resulting analysis can then be used as ateaching opportunity for assisting the golfer or a teaching professionalto analyze a golfer's swing. Though not illustrated, each object,gesture, or combinations identified using AI logic 108 can be providedas meta data or labels with a video captured by AMPS 100 such thatidentifying objects, gestures, kinematic, or combinations thereof can beprovided for subsequent media and video processing.

Although described as using AI logic 108 having golf logic, one canappreciate that various other activities, logic, and gestures can beused by AMPS 100 including, but not limited to, golf activity, footballactivity, soccer activity, baseball activity, basketball activity,skiing activity, snowboarding activity, biking activity, fishingactivity, boating activity, general sports activities, or various othertypes of non-sports activities that are predetermined to occur at ageographic location. AI Logic 108 can include objects important orrelevant to the activity. For example, AI Logic 108 can be used todetect football activities and can be used on a football field to detectobjects of a football player's number and name and a video can beprocessed using to aid in identifying video specific to a player name orplayers number. Various other objects for football or other activitiescan be provided by AI logic 108 depending on the activity or environmentAMPS 100 is being used.

As described above, AMPS 100 may be configured to use AI capable ofmachine learning and object/gesture identification based on an imagedata set. An image data set is a set of previously identifies objects,activities, gestures, or the like, that the AI can automaticallyidentify from images or video. An image data set may include a list ofknown objects and/or movements and may be used to identify a thresholdquantity of known objects based on captured images by AMPS 100, suchthat further instances of one or more of the known objects in the dataset may be automatically identified by AMPS 100 without requiringmanual/human identification after the image data set is defined. It willbe appreciated that AMPS 100 and AI logic described throughout thespecification is configured to automatically detect aspects of videoautonomously. AMPS100 can also include AI logic that can support otherforms of inputs such as audio inputs, sensor inputs, data inputs, voiceinputs, radar inputs or various other forms of supporting AI logic thatcan be used to detect inputs to AMPS 100. RMS 102 can include variousforms of inputs that can be used to initialize, record, process, anddistribute video that has been captured using AI logic 108. For example,RMS 102 can be used to identify a specific sporting event, such as golf,and initialize recording of a video of a specific golfer. RMS 102 canaccess AI logic 108, such as remote AI logic 110, specifically createdfor golf. Upon identifying a golfer using AI logic 108, video can berecorded for that specific golfer and processed using RMS 102 and NMS104. When a golfer is finished playing the hole, AMPS 100 can initiatefinal production of the golfer's video using NMS 104 and communicatedigital media to a media enabled destination 106 such as a golfer'smobile device or smartphone. According to an aspect, the final producedvideo can include the golfer, their name, the name of the course theyare playing, the hole number, logo of the course, and golfer statisticsfor the shot including a graphical ball trace that overlays the path ofwhere the ball travelled during the video. In this manner, no humanintervention may be needed to record, produce, and distribute videofootage thereby increasing the efficiency for video production whilereducing the time and cost associated with creating a final productionvideo having enhanced graphics and formatting.

According to a further aspect, media enabled destination 106 can includevarious types of devices capable of displaying digital media receivedform NMS 104 or digital media that is being streamed from NMS 104. Forexample, a media enabled destination 106 can include a mobile device(not expressly shown) such as a smartphone or other mobile devicecapable of receiving a link to video stored by NMS 104 and selecting thelink for playing a video. Media enabled destination 106 can alsodownload and store digital media at a destination. For example, mediaenabled destination 106 can include a web-based service, such as asocial media service provider, such as Instagram, Facebook, Snapchat,Twitter, and others capable of playing digital media produced by NMS104. In one form, a link to a video can be created by NMS 104 andcommunicated to a social media service. In other forms, a video requestfrom the service, such as Youtube, Disney+, ESPN+, Fox Sports, and otherstreaming services, may allow for storing video. In some forms, videomay need to be formatted prior to distributing to media enableddestination 106. According to a further aspect, NMS 104 may be able toprovide a digital media channel that can be accessed by media enableddestination 106. For example, NMS 104 can create a specific sportschannel, such as a golf channel, skiing channel, fishing channel, orother sports channel having specific types of digital media createdusing AMPS 100. As such, NMS 104 can provide various forms of digitalmedia and output digital media to one or more media enabled destination106 depending on the final use of digital media created by AMPS 100.

Referring now to FIG. 2 , a block diagram illustrating of a remote mediacapture system (RMS) is disclosed. Remote media capture system (RMS),generally illustrated at 200, includes processor and memory 302 whichcan include an NVIDIA Jetson AGX Xavier to process and control localvideo cameras. Specifications for the Jetson AGX Xavier can be found athttps://developer.nvidia.com/embedded/jetson-agx-xavier-developer-kit asof the filing date of the instant application. More than one computermay be used. In the case of a golf hole, one computer may be disposed ateach end of the hole. It will be appreciated that alternative computersystems may also be used as specific processing needs and performancemay change over time. Processor 302 can include a Dual-Core NVIDIADenver 2 64-Bit CPU and Quad-Core ARM® Cortex®-A57 MPCore, memory 303can include 8 GB 128-bit LPDDR4 Memory and can also include 32 GB eMMCof storage. Other processors and memory may also be used as needs andperformance may change over time. System 300 can also include AI enabledgraphics processor 216 which can include 256-core NVIDIA Pascal™ GPUarchitecture with 256 NVIDIA CUDA cores. Other graphics processors maybe used as performance and needs change over time. Operating software ofRMS 200 can include a Linux operating system, Python as an applicationprogramming language, and OpenCV image processing Library. RMS 200further includes AI logic 218 which can include a Machine LearningDeployment and Execution software such as Amazon Web Services GreengrassML software or other endpoint AI processing software or modules.

According to a further aspect, RMS 200 can include one or more remotecamera(s) 204 in communication with processor 202. Remote camera(s) 204,as described below, may be connected to processor and memory using anetwork interface (not expressly show). RMS 200 may further include apower module 220 configured to provide power to processor 202 and othercomponents of RMS 200. Power module 220 may be in the form of a batteryor combined solar powered battery, or may be a hard-wired connection toan AC or DC power source. Power module 220 can be provided to convertthe power source to one or more power levels as needed or desired by RMS200.

According to another aspect, remote camera(s) 204 can be connected usinga Power Over Ethernet (PoE) interface to provide power and communicationfor remote camera(s) 204. Other forms of connections can also be usedincluding, but not limited to, fiber optic, coaxial cable, twisted pair,single strand, custom cables, or various combinations thereof. RMS 200may further include communication module 214 connected to processor 202and a modem such as cellular modem, wireline modems or other forms ofmodems as needed. In one aspect, a cellular modem such as a Peplink MAXBR1 Mini may be attached to each computer (at each end of the golfhole). Specifications for the Peplink MAX BR1 Mini may be found at:https://download.peplink.com/resources/pepwave_max_br1_mini_lte_datasheet.pdfas of the filing date of this disclosure. For example, communicationmodule 214 can be configured with a wireline or wireless network capableof connecting the Internet or Cloud based services. Communication module214 can be used to determine the location or address to communicate withvia modem, and may further receive data or instructions for processor202. Communication module 214 with a cellular modem or hardwired modem,can be configured to communicate or transmit data via a network such asInternet or Cloud and as a cellular modem can be capable ofcommunicating using a 3G, 4G, 5G, or other communication standards. Inother forms, communication module 214 can be a wired modem capable ofcommunicating using a broadband connection such as Ethernet or via aFiber Optic connection, or various combinations thereof.

According to an aspect, RMS 200 may further include one or more remotecamera(s) 204 as AI enabled remote cameras that can process image datausing AI logic to detect a specific object or objects within video beingrecorded. RMS 200 can also include sensor input(s) 206 and audioinput(s) 208 that can be controlled or accessed by processor 202 to addadditional media to video being recorded using remote camera(s) 204.

RMS 200 can also include a digital media storage module 210 to store rawor compressed video, and data storage module 222 to store data files,operating files, control logs meta data, sensor data, radar data,session data, and other forms of data or information files. RMS 200further includes a media processing engine 212 configured to processmedia received by RMS 200 as described below. RMS 200 further includesan AI enabled graphics processing engine 216 accessible to processor 202and AI logic 218 that can be used to processes video, audio and sensorinputs to RMS 200.

During use, RMS 200 can be used to capture and process media contentthat can be processed and sent to a destination using communicationmodule 214. Portions or all of the processing can be performed locallyusing RMS 200. However in other forms, processing can be split betweenvarious portions of RMS 200 such as remote camera(s) 204, mediaprocessing engine 212, processor 202, and AI enabled graphics processingengine 216 and AI logic 218. Processing is also not limited to videoprocessing but can also include various combinations of processingincluding, but not limited to, sensor data processing, audio processing,data or meta data processing, graphics processing, AI processing,compression processing, or various other forms of processing that can beused to output digital media using communication module 214.

According to an aspect, RMS 200 can be used to process and compressmedia such that communication module 214 can communicate media to adestination in an efficient manner. For example, some cellular networkshave limited capacity for uploading media that contains large videoformats or files. As such, RMS 200 and communication module 214 candetermine a communication upload speed and bandwidth capability, andcompress media files to ensure a bandwidth demand is maintained. Variousvideo formats and media file sizes, such as 8K and 4K video, may be toolarge to communicate via a cellular network. As such, larger videoformats and resolutions can be transformed into smaller formats asneeded. For example, a 4K video can be transformed into an H.264 formatand uploaded as an HD, UHD or other digital media file format.

According to further aspect, RMS 200 can be used in a golf environmentto detect a golfer and record and communicate a golfer's activity in theform of processed video or digital media. During use of RMS 200 in agolf environment, processor 202 may be configured to automaticallycapture video data of a golfer using remote camera(s) 204, and processvideo using AI Enabled processing engine 216 automatically to create anautonomously processed video. For example, AI enabled processing engine216 can be used to detect a golfer using image data from the video and aneural network within AI logic 218 created to detect a person within avideo or image frame. Upon identifying the golfer, RMS 200 can captureand process video for that specific golfer. In other forms, AI logic 218can also include golf logic and gesture recognition logic (not expresslyillustrated) capabilities to process video data using RMS 200. Forexample, a AI logic 218 can detect a golfer holding a golf club and canfurther detect when a golf club has struck a ball. In this manner, thetime interval of when the golfer struck the golf ball can be identifiedand the recorded video can be segmented and processed accordingly.

According to further aspect, RMS 200 can use AI logic 218 to processvideo, audio, or sensor inputs. For example, AI logic 218 can includeobject identification capabilities that can be used to detect varioustypes of objects. Upon identifying an object within the video, AIenabled graphics processing engine 216 can be used to identify portionsof video having the identified object, and create a video segment onlyhaving that specific object. By way of example, RMS 200 can be deployedon a golf course and a golfer having a specific clothing, such as red,can be identified using AI logic 218. Video having a golfer wearing redcan be segmented until the golfer is no longer within the video.According to a further aspect, AI logic 218 can include golf logiccapable of identifying a golf object, such as a golf club, and a golferwearing a specific color, such as blue, within an image of the video.RMS 200 can then process the video having those two objects within thevideo to create a segment for those AI detected attributes.

According to a further aspect, RMS 200 can also processor other sensoryinformation to be used with the video to create media content that canbe combined and communicated using communication module 214. Forexample, audio input(s) 208 can output a time stamped digital audio filethat is in sync with a time stamped video file received from remotecamera(s) 204. For example, a microphone may be connected to audioinputs(s) 208 and can input audio that can be used to detect the soundof the ball being hit, or to detect speech or other audio from theplayers on a golf hole. RMS 200 can then combine the video and audiofiles to output media content having enhanced media appeal. In a furtheraspect, RMS 200 can combine sensor input data to recorded video tocreate an enhanced digital media experience. In other forms, sensorinput(s) may be stored in a sensor data file that can be communicatedwith video for additional processing by a network service as describedbelow. For example, sensor data such as weather sensor data can beobtained and used in combination with the recorded video. Sensorinput(s) 206 can include sensors including a wind speed detectionmechanism, temperature gauge, humidity, or other weather-related courseconditions.

According to another aspect, sensor input(s) 206 and a radar sensorinput or radar unit input capable of sensing various aspects of anobject traveling within a field of view of one or more remote camera(s)204. For example, a sensor input 206 as a radar unit input for golf candetect a golf swing, ball velocity, ball height, ball curve or variousother forms of radar data inputs that can be used to provide data thatcan be added to output digital media using RMS 200, or communicated toanother service that can further process the digital media and combinethe detected sensed radar data. The combination of camera and radar canbe used for sensing various aspects of a golf swing as well. Forexample, remote camera 204 configured as AI enabled camera may can beused to identifying small differences in the angles between two golfballs, as measured at the camera using optical zoom and pixel densitywithin the recorded video. When combined with radar having a wavelengthof, for example, 20 GHz radar or about 0.6 inches using phasedifferences. Camera inputs and radar input can share information aboutwhere objects are located and what kind of objects can be identifiedusing AI logic 218. For example, RMS 200 and an AI enabled camera can beused to identify an object using AI logic 218 and a radar input, havingthe same time stamp or recorded interval. RMS 200 can be used to providethe movement characteristics of the moving object within the videoframes using both AI enabled graphics processing Engine 216 and radarsensor unit data input to sensor input(s) 206. In this manner, anintelligent radar detection system that utilizes radar, imageprocessing, and AI logic can be deployed for efficient digital mediaprocessing and video enhancement.

According to another aspect, RMS 200 may use only one or more of remotecamera(s) 204 to detect AI objects within images captured using remotecamera(s) 204. For example, portions or all of AI logic 218 can bestored within remote camera(s) 204 and video having one or more objectsthat are relevant may be identified by remote camera(s) 204 and asubsequent video recorded and communicated to RMS 200. With camerasincluding AI logic 218, a reduced amount of video may need to berecorded and communicated to processor 202 for subsequent videoprocessing. Various forms of AI logic 218 can be used within remotecamera(s) 204 as discussed herein.

According to another aspect, RMS 200 may use no or only a portion of AIprocessing locally within RMS 200, and may use network or cloud-based AIprocessing remote from RMS 200. For example, RMS 200 may initiaterecording video locally using remote camera(s) 204. Recorded video canthen be communicated by RMS 200 to a remote processing system (such asNMS 104, NMS 400, or other cloud services) to perform AI processing ofcaptured video. In this manner, RMS 200 need only communicate mediahaving a specific format size using communication module 204 forsubsequent media processing, and the media file may then be uploaded tothe Internet or Cloud using communication module 204.

According to a further aspect, RMS 200 can process video locally near ageographic location of installed remote camera(s) 204 to provideautomatic monitoring and processing of a desired activity. RMS 200 canuse automatic detection and video recording/processing local to theinstalled sight of remote camera(s) 204 and processed video may betransmitted using communication module 214 to a destination. Forexample, a processed video may be received and forwarded to an end uservia an intermediate server or other communication device (not expresslyillustrated). RMS 200 can process video to add various graphicalelements to captured video. For example, media processing engine 212 canbe used to add information about a golf hole, such as the name of thegolf course, hole #, logo information, sensor data information, weatherinformation or various other forms of graphical data. According to oneaspect, a golf ball can be detected within a video frame and mediaprocessing engine 212 can add additional colored graphics to show thetrace or direction of a golf ball that has been hit, user information,course information and the like. Other elements can also be added usingRMS 200 as described within.

According to a further aspect, portions or all of RMS 200 can beincorporated into a mobile device having one or more integrated cameras.For example, a mobile phone such as a Samsung the Samsung Galaxy S21Ultra having four rear cameras, including a 108 MP f/1.8 main camera, a12 MP f/2.2 ultra-wide camera and two 10 MP telephoto cameras—one withan f/2.4 aperture and 3× optical zoom and one with an f/4.9 aperture anda huge 10× optical zoom can be used as RMS 200

In other forms, portions or all of RMS 200 can be incorporated intomobile phone cameras such as and iPhone 12 Pro created by Appleincluding a three camera system having an ultra-wide f/2.4 camera, awide f/1.6 camera and a telephoto f/2 camera. A front-facing camera witha 12 MP camera sensor is also provided. The mobile device includes aLiDAR scanner for low light conditions and a raw video processor forprocessing raw image and video files. Various other mobile deviceshaving cameras can also be realized as RMS 200.

Referring now to FIG. 3 , an AI enabled camera for use with a remotemedia capture system is disclosed. AI enabled camera, illustratedgenerally at 300, can be realized as various types of cameras as neededor desired and can be used with RMS 102, 200, 710, 1134, RMSs in FIG. 6, or various other remote media systems.

According to an aspect, AI enabled camera 300 can include an HD camera,UHD camera, 4K camera, 8K camera, 360 degree camera, 3D camera, 4Dcamera, Augmented Reality (AR) Camera, security camera, mobile devicesuch as a Samsung Galaxy s21 Ultra or an Apple iPhone 12 Pro, a dronehaving a camera such as DJI Spark Quadcopter, a GoPro camera capable ofconnecting to a mobile phone or other devices or various other digitalimage capturing devices capable of recording video.

According to one aspect, AI enabled camera 300 can be a UHD 4K cameramay be manufactured by Bosch Model MIC IP ultra 7100i camera havingspecifications and operating manual herein incorporated by reference. Inanother form, AJI enabled camera 300 can include an Hanwha, ModelPNP-9200RH having specifications and operating manual hereinincorporated by reference.

According to an aspect, AI Enabled camera 300 can include a processorand memory 302, a first camera sensor 304 such as a PTZ sensor, a secondcamera sensor 306 such as an optical zoom only sensor, and other sensortechnology illustrated generally as ‘n’ camera sensor 308 having avariety of different image capturing capabilities. AI Enabled camera 300also includes a control module 310 to control each of the camera sensorsand video storage 314 having memory for storing recorded video andimages. AI Enabled camera 300 also includes embedded AI Logic 316 thatcan be customized depending on use or activity to sense using AI. Forexample, Embedded AI logic 316 can include AI golf logic capable ofidentifying elements of a golf hole, player, tee box, green, a golf ballor various other objects. In other settings, other objects may beprovided within embedded AI logic 316 depending on the use for capturingand processing digital media including, but not limited to, sportingevents and outdoor activities. Although illustrated as embedded AI logic316, AI enabled camera 300 may be able to access AI logic stored remote,such as AI logic 108 at an RMS or NMS and the like to enable AIdetection of recorded images or objects.

AI Enabled camera 300 also includes a communication module 318 that canbe configured to use multiple types of communication including wirelessand wireline communication such as WiFi, Cellular, Ethernet, PoE, HDMI,RS232, 802.11, Bluetooth or custom communication interfaces. AI Enabledcamera 300 also includes a power module 320 configured to provide a oneor more power levels for powering AI Enabled camera 300, sensors andaudio microphones as needed or required. According to anotherembodiment, sensors 308 can include optical sensors and in some form caninclude various types or combinations of sensors, including, but notlimited to, optical, motion, infrared, radar or Doppler sensors,Bluetooth sensors, WiFi Sensors, RFID sensors, or various combinationsthereof and need not be limited to only optical sensing.

According to an aspect, AI Enabled camera 300 may be configured toinclude zoom functionality, including one or both of optical zoom anddigital zoom and may be further configured to have tilt and panfunctionality such that AI Enabled camera 300 may be pointed towards alocation. For example, AI Enabled camera 300 may each be pointed andzoomed at a tee box having a golfer attempting to tee off, and can beadjusted to follow and zoom in on a golfer for subsequent shots duringplay. Using AI logic, a camera can tag the specific user and follow theuser throughout their play. In an alternative aspect, AI Enabled camera300 may be a fixed view camera. In this aspect, AI Enabled camera 300may be configured to capture everything within its view and may alsodeploy digital and optical zooming capabilities without being rotatedalong an axis.

Referring now to FIG. 4 , a block diagram illustrating network mediaprocessing and management services is disclosed. Network mediaprocessing and management services (NMS), generally illustrated at 400,can include a network processor 402 connected to cloud storage andservices 404, which is connected to a communication interface 406configured to communicate with a remote media system (RMS) 450 or anyother remote video capture system or device configured to communicatevideo for processing and creating digital media. NMS 400 also includesan AI enabled graphic processing engine 408, an Image processor 410 andAI logic 412. Network Processor 402 can access various module ormanagers for processing, managing and communicating digital media andresources for supporting. For example, NMS 400 can include a remotemedia source manager 414, a session creation manager 416, a locationprofile manager 418, and a user profile and stats manager 420. NMS 400can also include a content/file manager 422, a video process manager424, a shot tracing module 426, a digital asset manager 428, and asensor data manager 430. NMS 400 can also enable use of a format manager432, an output manager 434, and a mobile app manager 436. NMS 400 canalso include a performance manager 438, an AI logic manager 440, and acourse manager 444. NMS 400 can output video received from RMS 450 asdigital media to a digital media enabled destination 448 using adistribution manager/communication interface 446.

According to an aspect, NMS 400 can also include an AI enabled graphicsprocessing engine or GPU 410 and video/image processor 408 configured toprocess video and images stored in cloud storage and services 404. Forexample, GPU 410 and/or image processor 408 can include various types ofAI enabled and image processors and in one form, includes one or moreNVIDIA V100 Tensor Core GPU capable of AI processing to generate anddevelop and train a Machine Learning (ML) for AI Logic 412 that can becreated, modified, distributed and used by NMS 400 or other AI enableddevices or AI logic described herein. According to one aspect, GPU 410and/or network processor 402 can also utilize additional software andservices to create AI logic 412. For example, GPU 410 can use AWSSageMaker for constructing, training, tuning, and evaluating ML models.Sagemaker supports a number of ML development frameworks and, accordingto one aspect, may use Keras/TensorFlow. Additionally, NMS 400 canemploy Sagemaker NEO to prepare AI Logic 412 models for deployment toremote processors and AI logic locations. Network processor 402 can useAI logic manager 440 to manage, distribute, update and delete AI logicdistributed to one or more locations multiple locations usingcommunication interface 406. For example, one or more golf courses mayhave independent AI logic 412 created for a specific golf hole. As such,AI logic manager 440 can maintain listings and version control of AIlogic 412 created and distributed by NMS 400 on a course-by-course andhole-by-hole basis.

According to an aspect, network processor 402, image processor 408and/or GPU 410 need not be viewed as single processors but should beviewed as multiple processors and services that can be accessed by NMS400 to process and output digital media, content, AI logic, and variousother outputs and services as described herein. For example, networkprocessor 402 can be realized as a cloud service that can be deployedusing Amazon Cloud Services, IBM Cloud Services, Microsoft CloudServices, or various combinations thereof and can access multiplemanagers and modules disclosed herein using network communicationprotocols capable. Cloud Storage and services 404 and distributionmanager/communication interface 446 can also include various types ofcloud storage services and distribution services having differentstorage capabilities and accessibility. For example, some content may bestored for immediate access while other forms of content can be storedfor delayed access using a deep storage technique. For example, cloudstorage and services 404 can include Amazon Web Services (AWS) Glacierfor storing video in the cloud. Additionally, content/file manager 418and distribution manager/communication interface 446 can utilize AWSCloudfront as a content delivery service that distributes videos to endusers.

According to a further aspect, video process manager 424 can be used toinitiate post processing of video received from communication interface406 and RMS 450. For example, a video may be modified or edited to addadditional graphical assets and formatted using a specific formatprovided by format manager 432. In one form, NMS 400 can employ formatmanager 432 for post processing and editing and may use Python andOpenCV for editing videos on AWS EC2 web servers operable with NMS 400.NMS 400 can also utilize AWS Elemental MediaConvert to convert or formatvideo prior to distribution using distribution manager/communicationinterface 446.

During operation, NMS 400 can receive a request to initiate a recordingsession using RMS 450. For example, a user having a valid user profilestored within user profile and stats manager 420 may send a signal toNMS 400 using a mobile app of a user. A request may be originated fromdigital media enabled destination 448 or from RMS 450. Location profilemanager 418 can also be used with user profile and stats manager 420 tovalidate the request and upon validating, a session can be created bysession creation manager 416 and sent to RMS 450 to activate a recordingsession using RMS 450 and associated devices. Session creation manager416 can store a session event using content/file manager 422 and when avalid video upload is initiated by RMS 450 with the valid session,content/file manager 422 can validate the upload and the video andassociated files/data can be stored using cloud storage and service 404.In one form, upon a video transfer being initiated, RMS Manager 414 cansend a disable event to RMS 450 to disable a recording of an event. Inthis manner, efficient use of resources at RMS 450 can be achieved and areduced amount of memory or local storage to RMS 450 may be needed.

Upon NMS 400 receiving an uploaded video, video process manager 424 caninitiate a post processing of an uploaded video stored within cloudstorage and services. For example, content/file manager 418 can includea file name and destination of a video upload, and can further obtainpost processing information to process the uploaded video. For example,an uploaded video can have a specific file name with meta data that caninclude the course name, location, hole #, user or golfer name, date andtime stamp, GPS data, file size, file type, processing completed,processing required, or various other video processing data that can bestored within meta data. Although described as being provided withinmeta data of the video file, a separate log file or video content filecan be provided as needed. Video process manager 424 can then processthe video using the meta data and other digital assets. For example, GPU410 can be used to add a banner at the top of the video including thecourse name, hole number, player name, number of shots and distance ofthe golf hole. Digital asset manager 428 can access digital assets andrequirements for a specific course and golfer. According to anotheraspect, video process manager 424 can access digital asset manager 428configured to manage various other forms of digital assets, graphics,text, logos, effects, marketing materials, promotional materials, orvarious other digital assets that can be added to a processed video. Forexample, an object corresponding to a particular brand, apparel type,club type, and/or swing type can be added to the video.

In another form, shot tracing module 426 can be accessed and used to adda shot trace to a golf shot within an uploaded video. For example, avideo can be processed using GPU 410, image processor 408, and AI logic412 to identify a golf ball within each from of the video. The framelocation of the ball can be stored within memory and a trace can beadded as an overlay to the video to show the direction the ball istravelling during playback of the video.

According to another aspect, sensor data manager 430 can be used withshot tracing module 426 to manage other graphical representations ofsensor data received from RMS 450 that can be added. For example, shottracing module 426 can identify a ball as described above and canfurther use sensor data to add graphics representing a swing or ballspeed, distance, ball flight, flight path, or various other sensor datathat may be added to video using video process manager 424. Performancedata from a radar unit of RMS 450 can be provided with sensor datauploaded from RMS 450. Sensor data manger 430 can access session dataand record time data to determine sensor data uploaded from RMS 450 andadd sensor data to the video accordingly. In other forms, sensor datamay be stored remote to NMS 400 and sensor data manager 430 may be usedto access sensor data acquired. For example, a third-party sensor, suchas a radar unit, may acquire sensor data at RMS 450. As such, sensordata manager 430 can access a third-party database, or third-party API,to acquire sensor data. In other forms, a third-party API can be addedto NMS 400 for accessing sensor data.

According to further aspect, digital asset manager 428 can be used toadd various colors to shots detected using shot tracing module 426 andsensor data manager 430. For example, if the ball travels above acertain speed, a red or “hot” color may be applied to indicate a highspeed, or a flame-graphic may be added as a tail to the ball. Similarly,if the ball flight is within a range of being considered “straight,” agreen color may be applied to the ball flight to indicate the lack of ahook or slice. Conversely, if the ball flight is not straight, anothercolor, such as yellow or red, may be applied to the ball flight toindicate a less than ideal shot. In one aspect, a golfer may indicate,via a mobile device and mobile app manager 436, the type of indicatorthey would like to have displayed. Other forms of processing an uploadedvideo may also be realized as described in various additionalembodiments herein.

According to another aspect, NMS 400 can use performance manager 434 toidentifying performance trends associated with a golf hole, course,players, or other detectable objects within video captured using RMS450. For example, performance manager 434 can analyze multiple shotsplayed at a hole and determine shot tendencies based on data frommultiple players. In other forms, AI logic 412 can analyze video toidentify a topology of a green and the overall make percentage based ona hole location on a green. AI logic 412 performing a green analysis canalso detect a direction a ball may break when putted from a specificlocation on a green. Performance manager 424 using AI logic 412 canidentify characteristics of a green through analyzing video and can alsodetermine shot tendencies a particular golfer and stored within userprofile and stats manager 420.

According to a further aspect, NMS 400 can use course manager 444,performance manager 436 and user profile and stats manger 420 to presentanalysis and playing suggestions and instruction between the player andthe course.

In another aspect, a method of providing statistics is provided. Themethod includes identifying data associated with at least one of a golfhole or players. The method further includes providing the dataassociated with the golf hole or the player. The method may includepresenting an average score on the hole, a rate of reaching the green inthe regulation for the hole, an average distance to the pin on the hole,or an average driving distance on the hole. The method may includepresenting a score of the player, presenting the rate of greens inregulation for the player, the average driving distance of the player,or the average distance to the pin for the player. The data may beassociated with a single round, a single day, multiple rounds, multipledays, a single player, and/or multiple players. The method may includecreating stats for players across a single hole or all holes played. Themethod may include providing a pin drop graphic in a video or arepresentation of the hole. The pin drop may corresponding to a singleplayer's shot(s) or for multiple players on the hole. The pin drop mayinclude a link to a video associated with a shot identified by the pindrop.

According to a further aspect, course manager 444 can be used tomaintain and update course information that can be used video processmanager 424. For example, course manager 444 provide digital assets thatcan be managed by digital asset manager 428 to be added to a videocreated at a specific golf course and hole. For example, logoinformation, course links, hole data, and location can be provided usingcourse manager 444. Course manager 444 can also be used to maintain aprofile for a golf professional located and working at a specificcourse. A profile description or bio of one or more golf professionalsfor a specific course can be maintained by course manager 444 and can beadded to one or more user interfaces using mobile app manager 436. Eachof the profiles can be toggled on/off using course manager 444, allowingthe biography information to be present within a mobile app. In thismanner, a local golf professional can be contacted using a mobile appassociated with a specific course.

Update Manager 442 may be used to push updates that are made at one ormore the above described managers or modules to one or more of the othermanagers described above, such that updated and modified informationremains up to date across the system.

Referring now to FIGS. 5A-D, graphical user interfaces of a mediaenabled mobile application is disclosed. The user interfaces of a mobileapplication are generally illustrated in FIGS. 5A-D and can be providedwithin an application that can be used, in whole or in part, on a mobilephone, tablet, smart watch, golf cart, pull cart, push cart, powered“follow-me” cart, laptop computer, or any other mobile device. It willbe appreciated that mobile application with user interfaces 5A-D mayalso be installed/embodied/accessible on other devices, such astraditional computers, internet browsers, and the like.

Referring now to FIG. 5A, an application home screen is illustratedgenerally at 500 and includes home screen interface 502 having currentweather conditions 504, and a video home background screen 506. Videohome background screen 506 can include a static image from a previouslyrecorded video or in some forms can include an animated video of auser's golf shot that was previously recorded. Home screen interface 502also includes a messaging banner 512 configured to communicate newmessages to app user's. For example, current course conditions can beprovided, a message from the golf course can be provided, advertisementsor specials at a course, messages from other golfer's or friends, orvarious other items or news items can be displayed within message board512. Home screen interface 502 also includes navigational elementsincluding a home screen icon 514, a courses icon 516, a check-in or scanicon 518, a my shots icon 520 with a bubble section, and an account icon522 including user profile information. Home screen icon 514 whenselected displays home screen interface 502.

According to an aspect, when a user selects courses icon 516, alocations screen interface 524 is displayed and includes a map view andlist view selector 526. When selecting a map view, a map 530 of courses532 having video recording technology is displayed on a map as a cameraicon. If a list view is selected, a list (not expressly illustrated) ofcourses can be provided. When a user selects a course 532, coursedescription screen 534 is displayed showing course details such aslocation, distance and directions 536, a golf hole description 538having the hole number, par and distance of the hole, one or more courselinks 540 that allow user's to access and book tee times on the course'swebsite. A flyover video or hole view section 542 provides a graphicalor video description of the golf hole having video recording technology.

According to a further aspect, mobile app may be used with course links542 to schedule tee times within locations screen interface 534 (notexpressly shown). Course links 542 may include a process paymentssection and may be configured to use adaptive pricing based on demand.For example, when demand is low, course links 542 with a tee timeschedule interface may automatically promote discounted pricing forplaying a round at the golf course.

According to a further aspect, when a golfer is playing a course havingvideo recording technology and they arrive at a hole, a golfer canselect the check-in or scan icon 518 to access check-in user interface544 illustrated in FIG. 5B. A first check-in user interface 546 caninclude a QR code image 548, a scan now icon 550, and a questions link553 describing where a QR code is located on the specific golf hole.When a user selects scan now icon 550, it's time for the golfer to taketheir shot, and second check-in user interface 554 displays a countdown556 of when video recording for the golfer. When the recording begins, athird check-in interface 558 is displayed indicating a tee off message560 and an animated recording icon 562 with a red dot blinkingindicating that the cameras are recording. When a player is done withtheir shot, a player can select a stop recording icon 564 to disablerecording. Each golfer can repeat this sequence to have the autonomousvideo technology record their shot.

According to an aspect, a QR code may not be available when a userarrives at a golf hole or another form of check-in may be deployed. Assuch, check-in user interface 546 can be updated to include a startvideo icon (not expressly illustrated). For example, the mobile app canbe used with location services to detect when a user arrives at a teebox and check-in or scan icon 518 can be selected and a start video iconcan be displayed within check-in user interface 546. As such, variousother check-in methods can be used and are not limited to only using aQR code to check in and begin recording a user's shot.

Referring now to FIG. 5C, a user interface 568 includes a graphicalrepresentation of a notification of a video being available. Userinterface 568 illustrates a message 570 sent to a user of a mobiledevice having screen 568. Mobile device can be the user or golfer'smobile device and screen 568 can be any portion of a mobile devicescreen configured to allow notifications, messages, in-app messages, ortext messages and the like to be displayed on a screen of a mobiledevice. In this manner, when a recorded video is finished beingprocessed and media is available, a user can receive a message thattheir video is available.

According to another aspect, a user may select my shots icon 520 to viewnew and previously created videos. For example, a my shots userinterface 572 can include an activity tab 574, a groups tab 576, and asearch video section 578 to search videos within my shots user interface572. A “new” label 580 is layered over a new video 582 to indicate if avideo is a new. Along with new video 582 is a shot description 584 thatcan include a course name, hole description and date when the shot wasmade and the video was recorded. According to a further aspect, my shotsuser interface 572 further includes a share icon 588 to share new video582 and a ReelTip icon 586 to share new video 582 with a local pro asdescribed below. Upon selecting share icon 588, a share user interface594 is displayed within user interface 592 of screen 590. Share userinterface 594 can include a share to social media tab 596 to allow auser to share to social media destinations such as Facebook, Instagram,Twitter and various other social media destinations. Share userinterface 594 also includes a watch my video tab 598 to launch a mediaviewer, a copy link to video tab 501 to allow a user to copy and send aunique video link via text, email, or other messaging capable of sharingvideo links. A user may also delete a video using a delete video tab503.

According to a further aspect, my shots user interface 572 also includesgroups tab 576 that can be selected within my shots user interface 572.Groups tab 576 when selected displays each of the groups a user playedwith when the user played that hole (not expressly illustrated) that avideo was recorded. For example, if a user played with three othergolfers, each of the golfer's name and a link to their shot can bedisplayed within the my shots user interface 572. Additionally, eachuser within the group can also leave comments within the groups tabsection and can further create a private “message board” that only theplayers that played together that day can view and edit. In a furtherembodiment as described below, each user can be added or deleted fromthe groups section automatically. For example, when a user checks in totake their shot using the check-in or scan icon 518, the mobile app canautomatically add each user profile to the group section of groups tab576 thereby creating an efficient way to share contact information,posts, comments, and other content with a group of golfers that playedgolf together that day.

According to a further aspect, groups tab 576 may be used to communicatewith golfers in a private group (not expressly illustrated). Forexample, each of the members of a particular group of golfers may havedownloaded the mobile app and each of the golfers having recorded. Theshots of each of the golfers may be aggregated and show privately togolfers within the private group thereby providing a series of shots foreach golfers to view and comment. In this manner, groups outside of asingle group can be created and displayed within a private group sectionthereby creating a private message board and social media platform forany size group of players playing the course that day.

According to a further aspect, when a user selects ReelTip icon 586 toshare a video with a local pro, a Reel Tip user interface 507 can bedisplayed to a user. Reel Tip user interface 507 can include a localgolf course logo 509 where the video taken, and a description 511 of howto get a tip on the video from a local pro of that course. Reel Tip userinterface can also include a first pro information tab 513, a second proinformation tab 515, and a third pro information tab 517. Proinformation tabs can be added or removed based on availability of a prothat day to provide a tip. Also, each pro information tab can include apicture section, a name and title section, and a small bio line. When auser selects a pro information tab, a pro information user interface 519for a selected pro is displayed. For example, when second proinformation tab 515 is selected, pro information user interface 519displays a pros name and bio section 521 which can include a brief bioabout the pro, an image 523 of the pro, and a share icon 525 to sharethe video with the selected pro. Upon selecting share icon 525, a shareselector (not expressly shown) can be displayed allowing a user to text,email, in app message, etc. the selected pro a link to the video. Inthis manner, a dialogue between a player and a local pro can be createdthereby decreasing a barrier of communication that can exist betweenplayers and pro which will allow the mobile app to assist with growingthe game of golf.

Referring now to FIG. 6 , a diagram of an AI enabled golf course isprovided. An AI golf (AIG) course, illustrated generally at 600, isillustrated as a multi-hole golf course and can include any number ofgolf holes, hole types, and facilities. For example, AIG course 600 canbe an 18-hole course, a 9-hole course, a 3-hole course, putting courseor any size course as desired. Further, AI enabled golf course need notbe a traditional golf course but can be provided as a golfing facilitythat can be used to practice or for entertainment. For example, AIenabled golf course could be realized as a driving range or practicefacility having multiple tee box locations and golfers hitting golfballs at the same time and video may be captured for each shot andprovided to golfers. In other forms, AI enabled golf course can berealized as an AI enabled golf entertainment facility, such as anoutdoor facility like TopGolf or an indoor facility such as Rokgolf andthe like. AI enabled cameras can be provided to record each bay and eachplayers video can be recorded and processed for all their shots asdescribed herein. As such, when a golfer leaves a facility, a video oftheir experience can be automatically created and communicated toplayers or participants mobile app or other destinations and/or socialmedia outlets as needed or desired.

According to an aspect, AIG course 600 also includes numerous radarunits that can be used in a variety of ways. Radar units describedherein can have single or multiple transmitters that can be used havinga high-frequency (10's of GHz) radio pulse that spreads out in a forwarddirection and a reflected pulse returns to the receiver and can bedetected by a radar unit. The unit can further have an array technologyon the receiving side that can detect a pulse that reflects back from agolf ball, or other object that's downrange using a vertical andhorizontal array of receiving elements. The timing of when the receivedpulse hits each receiving element depending on the angle between thatelement and the golf ball. The timing differences can be used todetermine the horizontal and vertical angles between the ball and theradar unit. The radar unit can also be used to measure downrange objectsthat can generate a reflected pulse including pins, flags, edge ofgreens, holes, bunkers trees, hazards, and the like. The received pulsesfrom moving objects are frequency-shifted by an amount proportional tothe speed of the object, or overall size. For example, a distance a ballis to a pin can be measured using a radar unit. A reflected pulse of agolf ball is different from the pin and when a moving ball comes to astop, the unit can detect the location of the ball relative to the pinlocation (each pin is moved daily to a new location).

According to an aspect, a radar unit can include a cone-shaped region infront of it in which it can ‘see’ golf balls. The region can cover anentire golf range by using multiple radar units. According to a furtheraspect, a radar unit can be used to detect a moving golf ball until itarrives on a green and slow to a stop. For example, a radar unit canalso identify that there wasn't a ball before and there is a ball now ongreen. The radar unit can measure the angle between the radar unit andthe golf ball, and they can also measure the distance to the golf ballrelative to the pin, which appeared in the morning after being moved butdidn't move all day.

When pairing a radar unit with AI enabled video, AIG course 600 allowsfor autonomous video processing that can use both radar input, videoinput, and AI to detect various aspects of a play on a golf course andoutput video footage specific to a golfer that may not otherwise havebeen output. For example, radar has limitations in that it cannotdiscern one specific golfer from the next, or pair a stuck golf ballwith a specific portion of video for a specific golfer. By using anintelligent system that uses video processing, AI, and radar to detect aspecific golfer and their play, a radar unit can be coupled within an AIenabled golf course system and create a unique experience for a golfer.

According to an aspect, AIG course 600 includes a first hole 601, assecond hole 602, a third hole 603, a fourth hole 604, and a fifth hole605. AIG course 600 also includes a water hazard 606, a creek hazard607, and a club house 608. First hole 601 includes a first hole tee box609, a first hole green 610 and a first hole fairway 611. First hole 601is realized as a Par 4 and includes a first hole tee box camera 612 afirst hole fairway camera 613, and a first hole green camera 614. Firsthole 601 also includes a first hole radar 615 covering the first holetee box 609 and fairway 611. First hole 601 also includes a first remotemedia system (RMS) 616 coupled to each of the first hole cameras and thefirst hole radar. RMS 616, and various other RMSs provided in FIG. 6 canbe provided as RMS 100 in FIG. 1 , RMS 200 in FIG. 2 , RMS 710 in FIG. 7, RMS 1124 of FIG. 11 or various other RMSs that can be realized on AIGcourse 600.

According to a further aspect, AIG course 600 also includes second hole602 including a second hole rear tee box 617, a second hole middle teebox 618, a second hole front tee box 619, and a second hole green 620.Second hole 602 is configured to be a Par 3 golf hole and include asecond hole first camera 621 aligned with rear tee box 617 and front teebox 619 to record golfers in either tee box and their shot to secondhole green 620. Second hole 602 also includes a second hole secondcamera 618 aligned with middle tee box 618 and green 620 to recordgolfers using middle tee box 618. It should be understood that eachcamera can be provided at different heights depending on the altitude orheight of each tee and green combination. Second hole 602 also include afirst green side camera 623, a second greenside camera 624 and a thirdgreen side camera 625 configured to record golfers from various angleson green 620.

According to a further aspect, AIG course 600 also includes third hole603 including a third hole tee box 626, a third hole green 628, and athird hole fairway 627. Third hole 603 is configured to be a Par 4 golfhole. Third hole 603 is configured to use first green side camera 623 asa tee box camera for third hole tee box 626. In this instance, when auser is on third tee box 626, first green side camera 623 can rotate,pivot and focus on a player on third tee box 626, leaving second andthird green side cameras to record action on second green 620. In thismanner, AIG course 600 can realize a cost savings in the number ofcameras needed or required to record play on AIG course 600. Third hole602 also includes a first green side camera 631, a second green sidecamera 632, a third green side camera 630, and a fairway camera 629.Second green side camera 632 is positioned to record third green 628 andvideo for fourth hole 604 as described below.

Referring now to fourth hole 604, second green side camera 632 can bealigned with fourth hole tee box 633 and fourth green 634 to recordvideo on fourth hole 604. Fourth hole 604 also includes a fourth greencamera 635 to record action on green 634 for fourth hole 604 and isprovided as a Par 3. RMS 647 is positioned between third green 628 andfourth hole tee box 633 and can be used to process video recorded ineach location. Additionally, fourth green camera 635 can be coupled toRMS 647 for processing and communicating recorded video on fourth hole604.

According to a further aspect, AIG course 600 includes fifth hole 605 asa Par 5 and include a fifth hole tee box 636, a first fairway landingarea 637, a second fairway landing area 638, and a fifth hole green 639.Fifth hole 605 further includes water hazard 606 to the right of fifthhole 605 and creek 607 positioned between first fairway landing area 637and second fairway landing area 638. Fifth hole 605 includes a fifth teebox camera 640, a first fairway camera 642, a second fairway camera 643and a fifth green camera 644. Fifth hole 605 also include a fifth holeradar 641 and a first fairway RMS 648 to process a first portion offifth hole 605 including tee box video, radar data, and first fairwayvideo. Fifth hole 605 also includes a second RMS 649 configured toprocess second fairway video and fifth green video captured during playof fifth hole 605.

According to a further aspect, AIG course 600 includes a power network645 capable of powering cameras, radars, RMSs and various other powereddevices at AIG course 600. It should be understood that power network645 is not limited to a single location and can be distributed on ahole-by-hole basis or to other locations at AIG course 600. Differentpower levels can also be provided and access as needed.

AIG course 600 can also include a driving range facility 650 including adriving tee location 651, driving range cameras 652, one or more rangeradars 653, and a range RMS 654. Additional cameras, radars, and RMSscan be provided depending on the overall size of driving range facility650. According to a certain aspect, driving range facility can be atraditional driving range with grass tees for tee location 651 and pinlocations within the range. In another form, tee location 651 can be adriving bay location that can be used for entertainment similar to aTopGolf experience. For example, user's can reserve a bay within teelocation 651 for a period of time and can practice hitting golf balls attargets within the driving range. In other forms, each bay can includeone or more screens (not expressly illustrated) to show animated mediaof shots. In a particular embodiment, each bay can be set up using AIenabled cameras as driving range cameras 652 to identify and recordspecific golf shots and process and output video to a video screenwithin each bay, or in other forms, send video to an end user of theirshot. Video can also be processed to add additional graphics such asanimation, VR graphics, and the like to video captured by driving rangecameras 651 to provide an enhanced media experience. Althoughillustrated as being a part of AIG course 600 it should be appreciatedthat driving range 650 can be a stand-alone facility that can beprovided as an entertainment facility such as Topgolf, Rokgolf, orvarious other golf entertainment facilities.

According to a further aspect, AIG course 600 can also provide video,including live video or recorded and processed video, to one or morevideo screens within clubhouse 608. For example, if a live feed of Hole#4 604 may be displayed on a television screen within clubhouse 608. Inone form, a daily closest-to-the-pin or hole-in-one competition can beplayed on Hole #4 604 and a live feed can be presented on a screenwithin the clubhouse providing entertainment for patrons after theirround. In some forms, a digital leader board may also be presentedwithin the video or as a part of a mobile application to show how closeor who is leading the competition.

According to another aspect, a video may be displayed when a playerarrives at clubhouse 608 so that players may view their shots once theyarrive. A player may have a location device that may be tracked withinAIG course 600 (such as via GPS in the golf cart, location data from themobile device, RFID tags, etc.), and in response to the players enteringclubhouse 608, recorded video specific to the golfers that arrived canbe displayed on a screen within clubhouse 608 such as arestaurant/19^(th) hole, bar and the like.

In other forms, a shot may be recorded at an entertainment facility,such as Topgolf, Toprange, Rokgolf and the like. Each bay can include adisplay that can output video captured of a player after their shot wasjust taken. Additionally, graphics can be added to the video and in someforms, a split screen can be provided with the video of the golfer onone side of the screen, and animated or graphics video of the shot (e.g.a top down view) being presented in another portion of the video screen.In this manner, players can view their actual swing with the ball flightand can tag their videos using a mobile device or other device havingaccess to the produced video for sharing, downloading, and viewing.

Referring now to FIG. 7 , an AI enabled golf hole is disclosed. AIenabled golf (AIG) hole, illustrated generally at 700, includes a teebox 702 and a green 704. AIG hole 700 is designed as a Par 3 golf holehaving a single set of tees illustrated. It should be understood thatadditional tees and tee boxes can be used and added to AIG hole 700 asneeded or desired. AIG hole 700 also include a first AI enabled camera706 positioned behind tee box 702 and a second AI enabled camera 708positioned behind green 704. Although illustrated as a two-camerasystem, additional cameras and/or AI enabled cameras can be added to AIGhole 700 as needed or desired. Additionally, first AI enabled camera 706can include a first camera field of view 732 and second AI enabledcamera 708 can include a second camera field of view 734. Each field ofview can be modified as needed prior to, during, and after use. First AIenabled camera 706 and second AI enabled camera 708 can be provided as aBosch Model MIC IP ultra 7100i and includes PTZ capabilities asdescribed above in FIG. 3 . Other cameras may also be considered.

AIG hole 700 also includes a remote media system (RMS) 710 positionednear AIG hole 700. RMS 710 can be connected to a network mediaprocessing and management services 714, illustrated generally as NetworkMedia Services (NMS) 714, and a media enabled destination 716 forcommunicating video or digital media to after capturing and processingusing AIG hole 700.

According to a further aspect, AIG hole 700 also include other devicespositioned near tee box 702 including a microphone 718 for capturingaudio, ball strikes, and player comments, a radar unit 720 for capturingdetails about a golfers' swing and ball flight, and a QR golf code 722that can be used enable use of AIG hole 700 for a golfer having a mobiledevice 724. In one aspect, QR golf code 722 is provided as a device. AIGhole 700 further includes a hole 726 positioned on green 704 andconfigured to hold a flagstick 728 having a flagstick height 730.

According to an aspect, first AI enabled camera 706 and second AIenabled camera 708 can be connected and powered by RMS 710. For example,RMS 710 can include a communication interface such as a PoE interfacecapable of connection multiple remote cameras while powering the camerasover an extended distance (in one example, the range for PoE is about100 meters, or about 328 feet). In one aspect, up to four PoE poweredcameras may be attached on one Main Computer. A Wi-Fi radio on the MainComputer that communicates with the computer at the opposite end of thehole may also be powered by PoE. Each PoE cable can be submergedunderground and connected to and powered by RMS 710. Additionally,Microphone 718 and radar unit 720 can be connected directly to RMS 710using a microphone cable, ethernet cable, fiber optic cable, coax cableor custom cables can also be used depending on the type of microphone orradar unit deployed. According to one aspect, first AI Enabled camera706 can also include an interface allowing for connecting an externalmicrophone or other sensors. Additionally, radar unit 720 need notconnected to RMS 710 separately but can be connected using acommunication interface of first AI enabled camera 706 and in one formmay be integrated into a housing with first AI enabled camera 706.Although described as connecting to first AI enabled camera 706, itshould be understood that one or more external devices can be connectedto second AI enabled camera 708 as needed.

According to an aspect, AIG hole 700 includes technology to allow forautomatic detection of a golfer to automatically record play of agolfer, process a recorded video, and communicate or upload a processedvideo in an efficient manner. AIG hole 700 can accomplish variousembodiments and combinations of embodiments to activate recording.According to one aspect, one or more of AI enabled camera(s) 706/708 canbe configured to detect the presence of one or more golfers within apredetermined area associated with AI enabled camera(s) 706/708. Forexample, first AI enabled camera 706 can be configured to detect using amotion sensor within the camera when a golfer is on tee box 702 andbegin recording video while a golfer is present on tee box 702.Additionally, second AI enabled camera 706 can be configured to use amotion sensor to detect when one or more golfers are no longer presenton green 704 and stop recording video in their absence. In one form,both cameras may be turned on or off together or independently when agolfer is detected at each location. Recorded video can be time stampedtogether and communicated to RMS 710 for further processing. In thismanner, a limited amount of video may be captured and recorded only whena golfer is present thereby reducing the amount of memory and processingneeded to store, process and communicate video on AIG hole 700.

According to a further aspect, AIG hole 700 can detect a presence of agolfer using wireless device, signal and services detection. Forexample, a golfer, golfcart, watch, mobile device, or other devices mayhave an RF, Wifi, GPS, Bluetooth, or location-based service capabilitiesand AIG hole 700 can be modified to accommodate one or more as needed.For example, a golfer may have an RFID chip capable of being detected byone or more devices of AIG hole 700. An RFID chip or RFID tag can beclipped to a golfer and tee box 702 can include an RFID sensor that candetect when the RFID tag is located near or on tee box 702. In otherforms, a golf cart can include GPS location-based services that can beused to trigger when a camera can begin recording or end recording basedon the location of the golf cart. In another aspect, a golfer may have aGPS enabled smart watch that can provide location or GPS services thatcan be detected by AIG hole 700. Location Services enabled devices suchas a mobile device, smart watch, golf watch, smartphone or tablet orother GPS or Location Services enabled devices to communicate a GPSlocation and AIG hole 700 can activate and deactivate cameras based onthe location of the GPS or location services device. In a particularform, a golfer may have a mobile device and mobile applicationconfigured to communicate with NMS 714 and provide GPS locations. NMS714 may store multiple GPS locations of AIG holes that can be used withthe mobile app on mobile device 724 for multiple golf courses. Upon auser actively using mobile device 724 at AIG hole 700, mobile device 724can communicate a location to NMS 714 and, upon validation of being ontee box 702, NMS 714 can send an activation signal or start event to RMS710 to activate first AI enabled camera 706 and second AI enabled camera708. As mobile device 724 leaves green 704, mobile device 724 cancommunicate a location to NMS 714 sufficient to send a deactivationsignal or stop event to RMS 710 to stop recording. In this mannerlocation services can be used to trigger recording and not recordingplay on AIG hole 700. Although described as having NMS 714 tracklocations of mobile device 724 it should be understood that RMS 710 canbe in communication with mobile device 724 independent of NMS 714.Additionally, one or more geofences can be placed around tee box 702 andgreen 704 sufficiently sized to activate and deactivate recording play.A Geofence is a form of location service that can be stored and modifiedwithin NMS 714 and mobile device 724 and NMS 714 can initiate activationand deactivation upon entry and exit of each geofence.

According to another aspect, a golfer may use mobile device 724 toactivate and deactivate a recording via a mobile application stored onmobile device 724. For example, when a golfer is about to take theirshot, they can use a mobile application and select a start record iconwithin the mobile application. The mobile device 724 can communicatewith RMS 710 and/or NMS 714 to activate recording using AI enabledcameras 706/708. When a golfer is done with their tee shot or after theyleave the green, a golfer can select a stop recording icon within themobile application and RMS 710 and/or NMS 714 can send a request to AIenabled cameras 706/708 to stop recording. In this manner, a golfer mayuse a manual start/stop to initiate recording on AIG hole 700, and RMS710 and NMS 714 can process the video for the golfer using a device orplayer identifier provided in association with activating the cameras onAIG hole 700.

According to an aspect, a golfer can be detected using AI Golf Logic 712of AIG hole 700. For example, mobile device 724 having a mobileapplication can be used to scan QR golf code 722 and AIG hole 700 canactivate one or more camera's in response to QR golf code 722 beingscanned.

In a further embodiment, upon activation of AI enabled cameras using oneor more of the techniques described herein, first AI enabled camera 706and/or second AI enabled camera 708 may take an image of the golfer thatinitiated the activation. Attributes of the golfer, such as clothescolors, skin tone, height, golf club, or various other attributes can becompared to AI logic having AI golf logic 712 that can be used tocompare AI logic 712 to the captured image. The results of thecomparison can then be used to actively record the golfer and to furtherprocess video having the AI logic comparison results. For example, theresults of the comparison can be stored in a log file, user file, AI logfile, or other storage file that may include a single entry for onegolfer, a series of entries for multiple golfers, or even a daily entryfor all golfers that played AIG hole 700. The file can then be used toprocess the recorded video and generate a video segment for each golferidentified. Upon a golfer no longer being detected at AIG hole 700, RMS700 can initiate a stop recording event for each of the cameras, and therecorded video can be further processed using AI Golf Logic 712 and RMS710 before being communicated to NMS 714 for further processing.

According to another aspect, a golfer using mobile device 724 caninitiate a recording using a QR code or QR Golf code 722. QR Golf code722 is QR code that are unique to Golf and includes at least one singlegolf hole identifier that can be used to activate one or more specificremote cameras that are positioned at a specific golf hole. QR Golf code722 includes embedded visual logic that can be deciphered by mobile appon mobile device 724 to allow for activating recording using the remotecameras located at that specific location. In the present disclosure,mobile device 724 can be used to scan QR golf code 722 using a mobileapp and capture QR golf code 722. Mobile device 724 can then send amessage to initiate a session for mobile device 724 and the user withthe unique identifier for AIG hole 700 to initiate a recording session.Mobile device 724 can communicate the message with unique credentials toactivate a recording at AIG hole 700.

According to a further aspect, QR golf code 722 and AI golf logic 712can be combined to activate, deactivate, and process recording for aspecific golfer. For example, a golfer can initiate a recording using QRgolf code 722, located at a specific location on AIG hole 700, and oneor more AI enabled cameras can take a photo of the golfer that can beprocessed and used to generate a video for the specific golfer. A userI.D. obtained from mobile device 724 can be paired with the image and AIgolf logic 712 can generate an AI log output specific to the golfer andused by RMS 710 and/or NMS 714 to process recorded video.

According to a further embodiment, QR golf code 722 can be combined withlocation services, GPS, motion detection, or other method of detecting apresence as a way to activate cameras and a recording session on AIGhole 700. Additionally, QR golf code 722 can also include an RFID taglocated underneath a printed or posted QR golf code 722. Mobile device724 when activated to scan QR golf code 722 can also activate an RFIDreader of mobile device 724. By activating an RFID reader, the QR golfcode 722 including a RFID tag can confirm that a user or mobile deviceis present near QR golf code 722. As such, an additional layer ofauthentication can be achieved prior to activating AIG hole 700 therebyobviating security risks or threats that may pose a risk to AIG hole700. Each RFID tag will be specifically created for each golf hole andwill have unique credentials that can be added to and communicated toNMS 714 to initiate and authenticate sessions.

According to another aspect, RMS 710 can be configured in a variety ofways to assist with on-course recording, processing and distribution ofvideos to NMS 714. Various aspects of a Remote Media System (RMS) aredescribed throughout the Figures and methods and can be realized by RMS710. For example, RMS 710 can be used to process various signals andimages to identify a valid golfer and initiate recording the golfer. Arecorded session can be processed by RMS 710 using video and audio inputto identify when a golfer strikes a golf ball, and further slicessegments of the video to create a processed video for the specificgolfer. RMS 710 also compresses videos to ensure efficient andcost-effective uploads of processed videos.

According to a further aspect, RMS 710 can serve as an agent andperformance manager of each of the cameras installed on AIG hole 700. Asan agent, RMS 710 negotiates the recording of video for specific golfersand communication between mobile device 724, NMS 714 and first AIenabled camera 706 and second AI enabled camera 708 using events thatare communicated between the devices. RMS 710 can also be used to logevents and performance other data of devices within a local network ofAIG hole 700 and can communicate log files to NMS 714 for remote accessand storage. RMS 710 can also store operating data for each device andinstallation and calibration data of each device connected to RMS 710.In one aspect, RMS 710 can include initial calibration data for eachcamera which can include a GPS location of each installed device such ascameras, radar units, microphones, QR codes, and other sensors. In oneform, the location or camera position can be obtained and used todetermine a distance to a flag on a green or a tee on a tee box. AIenabled cameras 706/708 can be calibrated with a reference device, suchas a yard stick, and a specific optical zoom of each camera can beobtained. The image of the yard stick, in combination of the number ofpixels obtained using the yard stick, can serve a reference fordetecting distances of objects within the field of view of the cameraand stored. By using the reference, as the flagstick 728 on green 704 ismoved along the green, the distance of the pin can be calculated basedon the number of pixels lost or gained at a certain optical level.Additionally, as the tees 736 on tee box 702 are moved, the distance ofthe tees to the camera can be determined and stored as well. Whencombined, the difference in distances (camera to tee) less (camera topin) can be used to determine the overall distance from tee 736 toflagstick 728. Various other objects and distances can be used by RMS710 to determine a number of distance.

In another aspect, each AI enabled camera 706/708 and/or radar unit 720can be used during a recording to capture details of a shot made by agolfer. For example, first AI enabled camera 706 can record a golfer'svideo and using the video, RMS 710 and/or NMS 714 may be used to add atrace over the video that shows the direction the golf ball was hit. Inthis instance, each frame of the video segment for the golfer can beprocessed, and the golf ball can be located in the frame using imagerecognition and AI golf logic 712. As the ball moves from frame toframe, the locations within the video can be identified and stored suchthat an X/Y coordinate system locates the ball within the frame. Theresulting X/Y coordinates can be used to draw the line the balltravelled within the recorded video. Depending on the distance traveledover a period of frames, and a height the ball reaches within eachframe, the overall speed of the ball and the height (apex) and curve(left/right) the ball travelled can also be determined.

In another form, radar unit 720 can be used with the video, orindependent of the captured video to detect the location and ball flightdetails, and communicate the details to RMS 710 and/or NMS 714 for videoprocessing. As described above, radar unit 720 can capture the speed,distance, height, and curve of the ball using radar technology andcommunicate the resulting information to allow for creating graphicsthat can be added to a video segment. One such system, such as theTrackMan Range, described in detail athttps://trackmangolf.com/products/range as of the filing date of thisdisclosure, made by TrackMan, can be used or other radar systems asneeded or desired.

Referring now to FIG. 8 , a method of activating recording using anautonomous media processing system is disclosed. The method may be usedby one or more of the systems, devices, processors, modules, software,firmware, or various other forms of processing to carry out the methoddescribed in FIG. 8 . Additionally, the method of FIG. 8 may be realizedas within various portions of FIG. 1-7, 9-11 , and in some aspects, maybe modified to include various functions, uses, and features describedtherein.

The method begins generally at step 800 and can be used at variousgeographic locations where a predetermined activity is to be performed.As one example, the method can be used for activation, video capture,and video processing on a golf course. At step 802, the method detectswhether a golfer has been detected at a golf hole. For example, a golfermay be detected as they approach a tee box in connection with playing agolf hole. Detection can be done in a variety of ways including usingGPS within a mobile, an RFID device, Wi-Fi detection, Bluetoothdetection, location services, radar detection, motion sensing, thermalor heat sensing or various other sensing technologies. In addition todetecting the presence of the individual golfers, similar transmittersmay be provided on a golf cart or the like, to indicate the presence ofone or more golfers. It will be appreciated that other detectionmechanisms may also be used. For example, in one form, a golfer'slocation services of a mobile device having an application for recordingvideo can be detected. For example, a geofence can be placed around aspecific tee box and when a golfer having a mobile app or other item totrigger the geofence can detect a golfer.

According to another aspect, at step 802 a user may scan a QR code usinga mobile app on a mobile device as described herein. The method be usedto capture the QR code and send a mobile device or app identifier andthe QR code having a unique identifier for the golf hole added to amessage to initiate a recording session. For example, the method may beused to combine a unique QR code with the a user or mobile identifier,and communicate the message to a service may have a uniqueidentification code and the user.

According to another aspect, at step 802 a golfer may be detected by auser selecting a record icon within a mobile app. For example, themethod can be used to monitor for a mobile device input that includes arequest to start recording. The method can send a message including therequest to validate that a golfer has been detected. In one form, themethod can combine a mobile app identifier and a location of the mobiledevice and communicate each to validate that a user is at a golf holehaving an AI enabled camera.

Upon detecting the presence of a golfer, the method can proceed to step804 and a session I.D. can be created for the golfer. A session I.D. isunique to the golfer and includes information specific to the golfer andcan include a unique I.D. for the golfer, a date and time stamp, alocation of the golf hole, and other items that can be used to create asession I.D. In one form, the method can be used to access a mobile appof the golfer that can have unique information about the user that canbe used to begin a session I.D. Once a session I.D. is created, themethod can proceed to step 806 and activate one or more AI enabledcameras at the specific golf hole and any associated microphones. In oneform, the method can include accessing a session I.D. that was createdand communicate the session I.D. as a valid I.D. for the specificgolfer. In this manner, an AI enabled camera and microphone can beactivated without having to manually start a recording at the camera, orhaving an individual at the camera.

In another form, at step 806 a camera and microphone can be activatedusing a scan of a QR code. For example, the method can include receivinga QR code identifier of the golf hole being played from the golfplayer's mobile device. The QR code identifier can be sent to RemoteMedia System or Network Media Processing and Management Services toactivate a valid scan or session. If the QR code identifier is valid, anactivation code can be sent to a local resource, such as an RMS or an AIenabled camera to activate recording video and sound.

Upon activating the camera and microphone, the method can proceed tostep 810 and captures an image of the golfer. For example, a golfer maybe located on a tee box and the activated camera may capture a image ofthe golfer. In another form, a golfer can activate the camera manuallyusing a start icon within a mobile app and the method can capture animage of the golfer. In another form, the golfer may have scanned a QRcode at a specific location near the tee box and the camera may capturean image of the golfer. For example, the AI enabled camera or RMS mayhave the GPS coordinates of the specific QR code being scanned and theAI enabled camera may pan, zoom, tilt, and focus at or near the specificQR code that may have been scanned with the session I.D. As such, animage of a golfer can be captured to be used to further identify thegolfer within a future video capture.

Upon capturing an image of the golfer, the method can proceed to step812 and the image can be compared to AI logic and/or a NN within an AIenabled camera, or an RMS local to the golf hole. In some instances, themethod can access a cloud-based service having AI logic and/or a NN tocompare the image. Various objects can be identified using AI Logic asdescribed herein. For example, a clothing color of a shirt, shorts, hat,shoes, pants, socks, skin tone, or various other colors of the golfercan be identified and tagged using the image. The tagged data can beprovided within the meta data of the image but in other forms may beprovided as an image file having image data, or can be provided with thesession I.D. of the golfer. In other forms, the method can be used toidentify golf objects a golfer may be holding. For example, the AI logiccan also include AI golf logic that can be accessed and the image can becompared to the AI golf logic to determine or identify the golfer. TheAI golf logic can include identify a specific club having a number, agolf ball, a golf tee, a tee box or various other golf objects asdisclosed herein. By identifying and tagging an image of objects of thegolfer using AI logic and/or AI golf logic, the method can then be usedto create a video specific to a golfer.

At block 816, the method continues to enable recording video using theAI enable camera at the tee box of the golf hole and can detect when agolfer enters the tee box. For example, after capturing an image of thegolfer at step 810, the AI enabled camera can pan, tilt, zoom and focusas needed at the tee box being played. The AI enabled camera can detectwhen a golfer enters the tee box. In one form, the stored AI objectidentifiers can be used to detect when a golfer enters the tee box. Inother forms, the AI enabled camera can mark a zone within an image frameas a valid location for the tee box and can detect when an activity mayoccur in the zone. A zone can be marked automatically after calibratinga camera during installation and marking the zone for the specific teebox. Multiple zones or tee boxes can be marked and stored within the AIenabled camera or RMS for use in detecting when a golfer enters the teebox.

Upon detecting the user, the method can proceed to step 822 and canvalidate the golfer on the tee box. As described above, various objectsmay have been identified at steps 812 and 814 and can be used toidentify the golfer when the golfer is present on the tee box. If agolfer is not valid, or may be a golfer that is not to be recorded for alack of I.D., the method returns to step 820 and detects when anotheruser may be present on the tee box. At block 822 when a valid golfer isdetected, the method proceeds to step 824 and records the golfer on thetee box. The method then proceeds to step 826 and determines if thegolfer has left the tee box. Various methods as described herein can beused to detect the golfer on the tee box. If the golfer has not left thetee box, the method proceeds to step 824 and continues to record thegolfer on the tee box. If at step 826 the golfer has left the tee box,the method proceeds to step 828 and stops recording the golfer.

Upon stopping recording, the method can proceed in two directions, oneprocess detects if another golfer is present and the other processes thecaptured video. Each of the processes can be done in a series or inother forms, can be done at the same time. In this manner, video of afirst golfer can be processed and uploaded while video of a secondgolfer can be captured allowing for efficient capture and processing ofvideo for each golfer and reduced delays of when a golfer may receivetheir recorded video.

As such, at step 830, the method accesses video and audio that wascaptured for the golfer and to step 832 to process the media. Forexample, the video and audio may be digital recordings that include timestamps for each frame. However, the frames may not be in sync with eachother. Additionally, the audio file or audio track for the specific timeperiod may not be overlayed with the video that was captured at the sametime. As such, each media file can be processed, aligned andincorporated into one media file as needed or desired.

Upon processing the media, the method can proceed to step 834 and candetect when a golf ball strike occurred. For example, the media file,video file, and/or audio file can be accessed to detect when a golf ballwas struck by the golfer. When accessing the video file, the method canscan the image data of the video file using image processing to identifya golf ball moving from frame to frame. The method can also use AI golflogic to detect a golf club at a specific location and a golf balldeparting from the specific location within the frame. In another form,the audio file can be accessed to listen when a golf ball may have beenstruck. For example, the method can include accessing the audio file tocompare or look for a golf ball striking sound and can identify thatspecific frame of when the ball was stuck. In another aspect, the mediafile, or both the video and audio file can be accessed to detect avisual image or frame of when the golf ball was stuck and an audio frameof when the ball was stuck. Upon identifying when the ball was stuck,the method can proceed to 836 and the beginning of a video segment canbe identified. For example, an average golf swing can take less than twoseconds. As such, a golf ball strike can be used to identify a 2-3second period or frame period prior to the ball strike. Additionally,the method can identify the frame when a golfer is leaves the tee box.In this manner, a beginning and end portion of the video can beidentified and the method can proceed to step 838 and slice the videointo a final segment. In this manner, a reduced version of the videothat was captured by the AI enabled camera can be created and uploadedin an efficient manner thereby increasing upload speeds and reducing thecost for uploading video. Although illustrated as slicing the videosegment in a certain way, it can be appreciated that other combinationsof identifying video and audio segments can be deployed with the overallbenefit of reducing the video and audio file sizes for subsequentuploads and processing. Various video formats and media file sizes, suchas 8K and 4K video, may be too large to communicate via a cellularnetwork. As such, the method at step 840 can process larger videoformats can be transformed into an H.264 format and uploaded as an HD,UHD or other digital media file formats as needed. The method can thenproceed to step 842 where the video can be uploaded to a networklocation for additional processing or to a destination. In one form, thesession I.D. can include a network destination for uploading a video foradditional processing by an RMS, NMS, or other device or service.Additional data files can also be uploaded using the session I.D.including, but not limited to, data files, operating files, controllogs, meta data, sensor data, radar data and other forms of data orinformation files that can be uploaded with the processed video.

At step 828, the method can also proceed to step 846 and detect ifanother golfer has been detected. If another golfer has been detected,the method proceeds to step 804 and repeats as needed. If at step 846,no additional golfers are detected, the method can proceed to step 848and the camera and microphone can be placed in an idle or reduced powerstate. The method can then proceed to step 800 and repeat.

The method of FIG. 8 can be configured in a variety ways or methodssequences in a particular embodiment, allows for efficient capture,process, and distribution of user experiences on a golf course. Themethod of FIG. 8 allows for detecting when a specific QR code is scannedat a golf course, and activating an AI enabled camera to identify agolfer, and to record and process the golfer's video using AI objectsand video slicing to create an efficient upload of a video with reduceddelays.

FIG. 9 illustrates a method of autonomous media post processing inaccordance with an aspect of the present disclosure. The method may beused by one or more of the systems, devices, processors, modules,software, firmware, or various other forms of processing to carry outthe method described in FIG. 9 . Additionally, FIG. 9 may be realized aswithin various portions of FIGS. 1-8 and 10-11 , and in some aspects,may be modified to include various functions, uses, and featuresdescribed therein.

The method begins generally at step 901. At step 903, when video isreceived form a remote video source, the method proceeds to step 905 toidentify an activity within the video. Various activities as describedherein can be stored within various AI logic that has been created usingMachine Learning as a Neural Network. Portions of the video can becompared to the AI logic and if an activity is not detected, the methodcan proceed to block 907 and process the video to identify a newactivity. In some forms, processing can include tagging or identifyingobjects within the video that are unique to an activity and can be usedby the Machine Learning for one or more activity. Upon processing thevideo, the method proceeds to block 909 to determine if a new activityshould be created within the Neural Network. For example, variousactivities as described herein can be identified but in some forms, asub-activity within an activity category can be created as well. Anexample of this activity can include, in one form of a golf activity, agolfer slicing or hooking a ball, a golfer throwing a club, a golferhigh flying another golfer, a golfer making a hole-in-one, or variousother activities or sub activities that may be created. If an activityshould be created, the method proceeds to step 911 and identifies theobject or series of objects that can be used and exist within an imageframe of the video. The method can proceed to step 923 and label theobject(s) identified and then to block 925 where the object or frame canbe added to the AI logic for that activity. In some forms, if theactivity exists, the object can be added to the Neural Network of theactivity, and in other forms, if the activity does not exist and aNeural Network is not available, the method can generate a new NeuralNetwork and Machine Learning instance to be used within the AI Logic.The method then proceeds to step 917 and processes the AI Logic and tostep 929 to determining if the activity is valid and can be releasedwithin the AI Logic. For example, the accuracy of a Neural Network caninclude dependencies on the number of objects identified and provided tothe Machine Learning instance for that activity. If only one instanceexists, the AI Logic will likely fail. As additional objects areidentified and used within the Machine Learning instance, the AI Logichas a statistically better chance of identifying the activity. Ifadditional objects for that activity are needed, the method proceeds tostep 901 until additional video is received. If at step 919 the activityis now valid, the Machine Learning instance can enable AI logic for thatactivity at step 921, and proceed to step 923 to distribute the AI Logicto various locations as needed. The method then proceeds to step 925 andends. The method may include zooming in on the video, zooming out on thevideo, or panning within the video, and the degree to which zoomingin/out or panning may be determined by the AI Logic based on detectedaspects of the video. The zoom and pan aspects may be performedautomatically.

If at step 905 an activity is identified, the method proceeds to step927 and determines if the video is valid to output or store. Forexample, a local video processor may have processed the video sufficientfor distribution. As such, a remote video processor, such as system 900can detect if the video requires any additional processing using dataprovided with the video. If the video is valid to output, the method canproceed to step 929 and format the video using a format manager. Forexample, a video may need to be formatted to be output to a mobiledevice or application having specific formats, file size, and otherspecifications required in connection with posting a video. Videoprovided to various locations and applications can include Facebook,Youtube, Instagram, Snapchat, and other applications. Each app beingutilized may require it's own formatting for publishing into a specificnetwork. As such, a format manager can determine one or more locationsfor the video and format accordingly. In other forms, the video can beprocessed to be distributed to a network location having a highdefinition or 4K video output on a stationary output device such as aspecific monitor. Various types of formatting may be used for the videoto output to various destinations. Upon formatting the video, the methodproceeds to step 931 and distributes the formatted video using adistribution manager. For example, the video may be a single instancethat is distributed to a cloud storage account configured to store thevideo. However in other forms, the video may have been formatted intomultiple formats, thus creating multiple videos that may need to bedistributed. As such, at step 931 the video is distributed to thosedestinations. The method then proceeds to step 925 and ends.

If at step 927 the video is not valid to output, the method proceeds toprocess the video. For example, the method includes 3 different types ofprocessing that may be used to process the video and are provided in noparticular order but only as a reference for illustrating processing ofthe video. At block 933, the method determines if one or more userprocessing needs to be performed. For example, a local video processormay have provided information for a specific user recorded in the video.As such, that information can be used to identify the user within thevideo. Various types of identification can be used including facialrecognition, geofencing, GPS or Location Services locationidentification, grid identification, manual input from a mobile app ofthe user, or various other triggers that can be used to identify thespecific user within the video. The method can also use AI Logic toidentify the specific user and characteristics, details, and/or objectsof that user can be provided with the video. Upon identifying the user,the method proceeds to step 937 and extracts segments of video as theyrelate to the user. For example, a user that is identified may be afootball player having a specific jersey number and name. The methodwould locate all segments of the video where the football player ispresent, and extract those segments from other players. In another form,a golfer may be playing a hole on a golf course with other players andthe video may include numerous other shots or activities taken by theother golfers. As such, the method can identify the specific user andactivity within various segments of video and remove the segments thatdon't include the user. In this manner, a video of just the golfer canbe created. Upon extracting the video segments, the method proceeds tostep 939 to determine if the end of the video has been reached. If ithasn't, the method proceeds to step 937 and repeats. If the video hasended, the method proceeds to step 941 and determines if the videoshould be processed for a new user. For example, as mentioned multiplegolfers or players may be a part of the same video captured. As such,when desired a new user can be identified at block 935 and the methodcan proceed as described above. In this manner, multiple segments thatare unique to a specific user can be extracted from a single videothereby reducing the number of video uploads needed for processing. Forexample, on a football field, a single video can be uploaded and themethod can extract the video footage for each player thereby creatingunique video segments for each player that can be provided to eachplayer, their teammates, coaches, and the like. Although at block 941multiple users may be detected, the method may not desire to extractvideo segments for all users and may include a profile from a profileand content manager to extract only certain user's segments.

If at step 941 the method determines that no additional user segmentsshould be extracted, the method can proceed to step 943. At step 943,the method determines if the segments require further processing. Forexample, if only a single segment of video is extracted, no additionalprocessing to combine segments may be needed. If at step 943 the videosegments require additional processing, the method proceeds to step 945and combines the segments for each user into a single video. Forexample, the segments can be extracted and stored as portions of a videoor video segments. At step 945, the segments can be combined together tocreate a single composite video for a user. Upon combining the segments,the method proceeds to step 947 and combines video segments for anyremaining user to create a video unique to each user. As such, anindividual participant can have their own video with segments createdfor their unique experience.

Upon processing the video if needed, the method proceeds to step 949 anddetermines if any effects need to be added to the video. For example, acontent manager, such as the content manager 818 in FIG. 8 or otherautonomous content manager, may identify a video of a golfer that wasplaying a certain golf hole at a resort such as Omni Barton Creek. Thecontent manager may have stored an introductory video of a drone flyoverof the golf hole being played and may add the introduction video to theuser's video segment. In other forms, animated graphics illustrating thedistance to the hole can be drawn from a tee box to the green from a‘top down’ view of the hole. Other effects can also include adding audioor additional captured video of the user and other players at theactivity. In one form, portions of a segment of the video may beidentified or tagged to add a tracer to the movement of the ball as apart of creating effects. In other instances, AI Logic can be used todetect when a ball is located around the green in a location that is notdesired by the golfer. In that instance, an augmented effect can beadded to the video when a ball goes into the woods, a sand trap, a waterhazard and the like. An augmented effect can include an animated videooverlay. For example, an animation of a Loch Ness Monster stealing thegolf ball as it enters the water hazard can be added to the videosegment. Other animations can also be used and added as needed ordesired. In this manner, an augmented reality can be added to the videofor the user. According to a further aspect, the video may add a balltracing effect to a shot made by a golfer. For example, the method canbe used to identify a golf ball within the frames of the video and add acolored trace line to each frame to show the path of the ball. If thevideo includes video segments of the ball coming into the green, thetrace can be added to the video as ball lands onto the green. In someinstance, AI logic or image processing can be used to locate the ball ina frame and, in some cases, the video may be reversed after the ball islocated on the green. For example, when a user approaches his or hergolf ball on the green, AI logic or image processing can identify theuser and add effects or other content prior to the user picking up theball or addressing the ball. In this manner, through reverse processingof the video data, the ball can be traced back in previous frames orsegments and the video can be modified for that specific useraccordingly. In another form, an effect can include audio effects,music, or sound added to the video. For example, music can be addedthroughout all or portions of the video and can include various audiolevels. Unique sounds can also be added to the video based on what ishappening in the video. For example, a user may hit the ball into thewoods and a ‘chainsaw’ sound, clapping sound, laughing sound, applaudingsound or other sound effect can be added to the video segment. Inanother form, AI Logic or image processing can be used to identify whena golf ball goes in the cup and a ‘ball dropping in the cup’ soundeffect can be added. Effects can be predetermined based on the activityor sub-activity identified by the AI logic. In this manner, the methodcan access a label within a video segment and automatically add theeffect desired to portions or segments of the video.

After adding an effect if desired, the method proceeds to step 953 anddetermines if graphics need to be added to the video. If no additionalgraphics need to be added, the method proceeds to step 929 and ends. Ifadditional graphics are to be added, the method proceeds to step 955 andobtains the content or graphics to be added from and assets resourcesuch as assets 914 using content manager 418 of FIG. 4 or other asset orcontent resources as needed or desired. Assets or graphics can includeone or more graphic to add to a video image or video segment. Forexample, graphics can include information such as the name of thegolfer, the date, the golf course, the hole #, the distance to the hole,the club used by the golfer, current weather conditions, the max heightof the ball or after it is hit, the speed of the ball after it is hit,the curvature of the ball during flight, the max distance the balltravelled, the current stroke or number of strokes taken, the par forthe hole, other player info currently playing with, or other playerinformation or course information as needed or desired. According toanother aspect, the golf course can include graphical assets to be addedto a segment of the video such as the name of the golf course, a logo ofthe golf course, the age or when established, the current pro's name,the owners name, or various other types of marketing assets or graphicsthat a golf course may desire to be added to a video segment. Althoughdiscussed as adding assets for the golf industry, other graphical assetscan be added to the video as needed or desired. Upon obtaining thegraphical assets the method proceeds to step 957 and modifies thesegments adding the assets or graphics to specific video image orsegments. The method then proceeds to step 929 where the method ends.

The method of FIG. 9 can be modified as needed to combine or removevarious portions as needed. For example, upon identifying an activity orsub-activity at step 905, the method can be used to segment video andfurther process the video segments to identify a sub-activity. Thesegment can be labeled as having that sub-activity and a label can befurther used to process the segments, add effects, add graphics, orvarious other types of processing of the video segment. In this manner,an automated process using AI Logic can efficiently edit and process avideo without the need for having an individual modify and edit a videomanually.

If the video is valid to output, the method can proceed to step 929 andformat the video using a format manager. For example, a video may needto be formatted to be output to a mobile device or application havingspecific formats, file size, and other specifications required inconnection with posting a video. Video provided to various locations andapplications can include Facebook, Youtube, Instagram, Snapchat, andother applications. Each app being utilized may require it's ownformatting for publishing into a specific network. As such, a formatmanager can determine one or more locations for the video and formataccordingly. In other forms, the video can be processed to bedistributed to a network location having a high definition or 4K videooutput on a stationary output device such as a specific monitor. Varioustypes of formatting may be used for the video to output to variousdestinations assets 914 using content manager 418 of FIG. 4 or otherasset or content resources as needed or desired. Assets or graphics caninclude one or more graphic to add to a video image or video segment.For example, graphics can include information such as the name of thegolfer, the date, the golf course, the hole #, the distance to the hole,the club used by the golfer, current weather conditions, the max heightof the ball or after it is hit, the speed of the ball after it is hit,the curvature of the ball during flight, the max distance the balltravelled, the current stroke or number of strokes taken, the par forthe hole, other player info currently playing with, or other playerinformation or course information as needed or desired. According toanother aspect, the golf course can include graphical assets to be addedto a segment of the video such as the name of the golf course, a logo ofthe golf course, the age or when established, the current pro's name,the owners name, or various other types of marketing assets or graphicsthat a golf course may desire to be added to a video segment. Althoughdiscussed as adding assets for the golf industry, other graphical assetscan be added to the video as needed or desired. Upon obtaining thegraphical assets the method proceeds to step 957 and modifies thesegments adding the assets or graphics to specific video image orsegments. The method then proceeds to step 929 where the method ends.

According to another aspect, at step 953, the method can also includepost-processing to include graphics or video enhancements. In oneaspect, the player's name may be provided on the screen prior to theirshot. In another aspect, the player's score may be provided on thescreen. In another aspect, the club being used may be displayed. Variousother graphics may be overlaid on the screen to provide a videoresembling a professional broadcast. The graphics overlaid on the videomay include various data associated with the player or the shot beingplayed.

FIG. 10 illustrates a method of using a media enabled mobile applicationaccording to an aspect of the disclosure. The method can be used tooutput user interfaces illustrated in FIGS. 5A-D and can be providedwithin an application that can be used, in whole or in part, on a mobilephone, tablet, smart watch, golf cart, pull cart, push cart, powered“follow-me” cart, laptop computer, or any other mobile device. It willbe appreciated that mobile application with user interfaces 5A-D and themethod or FIG. 10 may also be installed/embodied/accessible on otherdevices, such as traditional computers, internet browsers, and the like.

The method begins generally at step 1000 where the method proceeds todisplay a UI and background processing within a mobile application. Aseries of decision trees can be activated upon launch the method of FIG.10 and can be activated by selections within a user interface orprocesses running within the mobile application. Each decision tree willbe described in response to the activation and need not be deployed inthe order presented within FIG. 10 and can be deployed in multipledifferent orders. Additionally, an “A” with a circle illustratelocations to loop from and to locations within the decision treesequence illustrated. Other loops can also be used as needed or desired.

At decision block 1002, if a home button within a UI of a mobile app isselected, the method can proceed to step 1014 and a background image oranimation of a golf shot can be displayed within a user interface. Theanimation can be portions or all of a media file created using MMS 100or other media processing systems provided herein. In other forms, auser can tag a video to be presented as a background animation for thehome screen. Upon displaying the home screen, the method proceeds tostep 1016 and obtains local weather data using a weather service basedon the current location of the mobile application. Upon obtainingweather conditions, they may be presented at step 1018 within the homescreen of the mobile app. The method then proceeds to step 1020 anddetermines whether a new message may be available to be presented withina message area of the home screen. Messages can be provided from golfcourse, other golfers, weather messages, and other forms of content. Inother forms, messages can also include notifications from other golfers,notifications from the mobile app provider about new course openings,regional golf information, links to golf videos or daily or weekly golfvideos created, and various other types of media content that can bepresented to a golfer. If a new message is available, the methodproceeds to step 1022 and displays the new message within the homescreen. If a new message is no new messages are available, the methodproceeds to display the home screen without a current message.

At decision block 1004, if a locations icon is selected within a mobileapp, the method proceed to step 1024 and a map view of locations havingAI enabled golf courses are displayed within a location map of themobile app. For example, a the mobile app can access Google maps anddetermine a GPS location of a golf course having AI enabled technology,and add a graphical icon of a camera that can be selected within the mapview. The method can then proceed to decision step 1026 to detect if alist view of AI enabled golf courses was selected. If a list view wasnot selected, a map view continues to be presented within the userinterface. If a list view is selected, the method proceeds to step 1028and displays a list of available golf courses. The method then proceedsto step 1030 an detects if a location has been selected. If location hasnot been selected, the method proceeds to display the list view or themap view that was previously chosen. If at step 1030 a location isselected, then the method proceed to step 1032 and displays coursedetails of the AI enabled golf course. For example, course details caninclude the name and location of the course, website or tee timepurchase site, a golf hole description of the hole including yardage, agraphic of the hole, a drone flyover, or other hole information. In oneform, if a hole has one or more competitions such as a closest-to-thepin, hole-in-one, longest drive, or other competitions, the payoutamounts for a specific hole, competition, and terms can be presented. Insome instances, more than one golf hole at a course may have acompetition and a list of golf holes and payouts may also be presentedwithin the user interface.

At decision step 1006, if a check in or scan icon selection is detected,the method proceed to step 1034 and displays a check in or scan icon fora golfer to select when they are present at a golf hole having an AIenabled camera. The method then proceeds to step 1036 and detects if theQR scan button is selected. If the button is not selected, the methodproceeds to step 1034. If the QR scan button is selected, the methodproceeds to step 1040 and creates a session I.D. for the mobileapplication and user. For example, a Session I.D. can include a mobilephone identifier, a user identifier, date and time, location, of themobile. Upon creating a Session I.D., the method proceeds to step 1042and access the mobile phones camera and opens the view finder to allow auser to scan a QR code present at the golf hole. A QR code will bepresented near a tee box of a hole being played. The QR code is a uniquecode is generated for a specific hole on a specific golf course at aspecific tee box, and can also include an RFID tag embedded underneathto further assist with authenticating a QR scan.

In another form, at decision block 1044, if a golfer scans the golfcode, an AI Enabled camera at the golf hole can capture an image of theindividual and process the image using AI to identify or tag the golfer.In addition, the method can add a time stamp to the session I.D. and theAI enabled camera can add a time stamp to the image captured. The methodcan then proceed to provide the session I.D. and have the image capturedtagged with one or more identified objects of the golfer, such asclothing color, height, skin tone, or various other attributes that canbe identified using AI logic. The image data can be used by the AI logicand a NN to detect features of the golfer.

Upon scanning the QR code at step 1044, the method proceeds to step 1046and detects the unique I.D. within the QR code for the Golf hole andproceeds to step 1048 and sends a message to the AI enabled camera tobegin recording the golfer. The message can be communicated via thesession I.D. and can include the unique I.D., a player name or I.D.,date and time stamp, detected A.I. attributes or features, or variousother types of data that can be used to initiate a recording of thegolfer. The method can then proceed to step 1050 and initiate a countdown in seconds of when the user should take their shot. Although assuggested, the AI enabled camera is already recording, providing acountdown provides a golfer a time table to initiate hitting their shot.Once the countdown reaches zero, the method proceeds to step 1052 anddisplays a recording image with a blinking icon to indicate that thecameras are recording the shot. Also at step 1052, the user interfacewill show a stop recording icon to allow a user to stop recording theshot when the shot is done. The method can then proceed to step 1054 anddetect if the camera should stop recording the shot. For example, a usercan select the stop recording icon and a message can be sent to the AIenabled camera to stop recording the user. In another form, a user mayforget to select the stop recording icon. If needed when this occurs,the method can include detecting when a second user start a new session,can use a time interval such as 1-5 Minutes to end the session. In otherforms, the method can also use the AI enabled camera to detect if theuser is present on the tee box, or a motion sensor to detect if there isno one present on the tee box any longer. The method can also use theGPS within the mobile phone to detect if a user is walking away from thetee box and in some forms can use an accelerometer within the mobiledevice to detect if a user is walking or riding in a golf cart. Variouscombination of methods described above can be used to detect when a useris present or not present on the tee box. Upon detecting a lack ofpresence, the method proceeds to step 1054 and stop recording by sendinga signal to the AI enabled cameras, and then proceed to step 1056 andend the recording session.

At decision step 1008, when a my shots icon is selected, the methodproceeds to step 1058 and identifies if a new video has been received.If a new video has been received, a “new” bubble icon is added to afirst image of the video, and the method proceeds to step 1060 andpresents a list of videos to a user within the user interface. In oneform, the videos can be presented in a list view with the newest videoat the top of the list. In other forms, the list can be presented aftera search, or in other forms presented as oldest to newest. In anotherembodiment, the method can be modified to include a groups icon thatwill allow a user to view various groups, videos, and message boards forgolf shots made. For example, a group can include each of theindividuals that took a shot with the user that day. However, in otherforms, it can include groups that all may have played the same golfcourse that day. In other forms, a group can be a select group ofgolfing buddies that may be playing various other courses and want toshare video with the user.

Upon displaying a video list, the method proceeds to step 1062 anddetects whether a video has been selected to be viewed. If a video hasnot been selected, the method proceeds to step 1060. If a video has beenselected, the method proceeds to step 1064 and a video player can beactivated to view the selected video. The video player can be a playerresident to the mobile device. In other forms, the video player can be anetwork-based video player that can be used to play videos on a mobiledevice. Additionally, the player can include various controls to allow auser to stop, start, pause, scrub, mirror, and download the selectedvideo. Various other actions can also be used while watching the video.Additionally, the player need not be ‘activated’ until the user selectsthe play button and can be presented within the user interface withother selectable elements and content such as illustrated in FIG. 5C.

Upon launching the video player, the method can then proceed to step1066 and detect whether a share icon has been selected. For example, ashare icon can activate a list of destinations that can be selected tosend or share a video to. The destinations can include, but are notlimited to, any app available to a user's mobile device in share modesuch as Facebook, Instagram, twitter, Snapchat, Pintrest, Youtube, thecurrent app, or other apps as needed or desired. A destination can alsoinclude saving the app locally to the mobile device or with a cloudservice for storing videos and photos. The method can also includepresenting a watch my video selector, copy video selector, a copy linkselector, and a delete selector to delete the video. At block 1068, themethod can also display a share with a pro icon within the userinterface. A share with a Pro icon allows a user to select a local golfprofessional at the course the video was captured to share with. Forexample, the video can include a location I.D. where a video was taken,and a local pro can for that golf course can be shared with to obtain agolf tip on the video.

At block 1070, a share selection is detected, the method proceeds tostep 1072 and detects if a share with a pro icon has been selected. If ashare with a pro icon is not selected, the method proceeds to step 1080and identifies the selected destination, and shares a link to the videoto the selected destination. In one form, the method can add defaulttext for the video such as “Look at my hole in one!”, “Here's my shotfrom Pebble Beach!”, “Hanging with my buds at TopGolf! ! !”, or variousother messages that can be created as a default based on the locationthe video was taken. In other forms, a user can provide their ownmessage to add to the video link and can send the link to the desireddestination.

If at step 1072, a user selects to share with a professional, the methodproceeds to step 1074 and displays a list of professionals that arelocal to the course where the video was taken. For example, a golfcourse may have multiple professionals and list of each professional forthat course may be presented. In other forms, the method can be modifiedto only present a list of professionals that may be present at thecourse that day, or may want to be a part of providing tips to golfers.In another form, there may be no professional present and the share witha pro icon may not be presented within the user interface, or an emptylist may be presented with a “come back soon!” or similar message withinthe user interface. Upon a user selecting a pro if available, the methodproceeds to step 1076 and detects which pro to share with, and then tostep 1078 and sends a link of the video to the selected pro. The linkcan be sent via a text message, email, in-app message, notification orvarious other communication and can include a message such as “Jon Luxshared a video and would like a free tip!” or various other messagesthat can be modified or added. In one form, the message can be sent as atext message which may or may not include the actual mobile numbers ofthe sender and/or receiver. The method can be modified to allow a useror pro to not allow their mobile numbers to be shown as a part of thetext message. This method can also be used for email, in app messaging,notifications, or various other forms of communication.

At step 1010, when a profile icon is selected, the method proceed tostep 1080 and displays account icon and to block 1082 and displaysprofile icon for the user. At step 1084, if the account icon isselected, the method can proceed to step 1086 and displays a user nameand password section and then to step 1088 and displays a paymentinformation section. The method can then proceed to step 1090 and if auser selects a section to modify, the user can modify the selectedinformation. For example, a user can enter a new user name, password,email address, privacy settings, or other various other types of accountinformation. In one form, the method can also provide a terms andconditions link with the terms and conditions that can be viewed oraccessed by the user. According to another form, a user can add paymentinformation as a part of their account information. For example, paymentinformation can include traditional payment such as credit cardinformation but can also include other payments such as Venmo, Paypal,Bitcoin, or various other payment methods. Payments methods can be usedto pay for rounds of golf scheduled via the mobile app, competitions orgames such as closest to the pin, hole-in-one, longest drive,competitions. Payments can also be used to pay for individual or groupbets that may be played on the golf course between the user and otherusers. If at step 1090 an account is modified, the method proceeds tostep 1092 where the new account information can be verified and saved.

If at step 1084, an account section is not selected the method canproceed to step 1086 and detect if the profile section is selected. Ifthe profile section is not selected, the method can proceed to block1080. If at step 1086 the profile section is selected, the method canproceed to block 1094 and display the player profile for the user. Aplayer profile can include a player image or photo, a player name whichcan be different than a user name in the account section, a birth dateor month/year, a handicap, a number of rounds of golf per year played, apreferred tees such as pro tees, men's regular, senior tees, juniortees, ladies tees, or other tees. A player profile can also include whatball a player likes to use, and a “What's in the Bag” section which caninclude the name and types of clubs, putters and wedges the golfer isusing. For example, a golf may be using a Callaway Driver, TitleistHybrid, Mizuno Irons, Volkey Wedges (52 and 60 degree), and a ScottyCameron Putter. Various manufacturer's can be presented to a golfer whensetting up their player profile. Portions or all of the player profileinformation can be added as media information to the video created foreach user. Additionally, player profile information can be stored withina database and used to detect information about each player that can beused to market new products and services to the player depending ontheir player profile. In this manner, the database can be used to informusers of new products and services that can help a player improve theirgame and can also serve as a platform for product and service providersto market to. Upon modifying the player profile, the method proceeds tostep 1098 and updates the profile. In one instance, the method can bemodified to allow a user to send a share the new profile to a selectdestinations if a user updates portions of their profile. For example, auser may want to share that their handicap changed or they just bought anew driver or putter. Various elements of the plyer profile can bechanged and shared as needed or desired.

If at step 1012 a new video is received, the method proceeds to step1001 and sends a message to the user's mobile device. The message can bea text message, in-app message, notification, email, messenger app text,or various ways to message that a new video is available to view. Themethod can also proceed to step 1003 and a badge associated with themobile app can be modified to show a new video is available. Forexample, the app name and logo can be updated to show a number of newvideos that may be available within the mobile app. In another form, thenewest video can be added to the mobile app as a link and an in appicon, such as a my videos or my shots icon, can be updated with thenumber of new videos. Within the my videos or shots section, a “New”bubble reference can be presented as a partial overlay to the videoimage of the new video. According to another aspect, step 1012 can bemodified to include or add messages. The method can be used to send amessage to one or more groups within the mobile app that a new post orvideo has been uploaded. For example, if a user is included within agroup share of the mobile app, a message of an available video for oneor more users can be sent to the others within the group to indicatethat a video is available. The group message availability can also beadded to the app icon or my shots icon as a separate bubble icon havinga different color and location on the icon. In this manner, golfer'swithin a group can communicate messages and videos with each other aboutvideos, shots, competitions, or other messages without having to use athird party messaging platform thereby keeping the overall golfexperience within the same app on a mobile device.

FIG. 11 illustrates a block diagram illustrating a multi-view AI enabledgolf hole according to an aspect of the present disclosure. A multi-viewAI enabled golf hole (MAIG hole), illustrated generally at 1100,includes a tee box 1102 having multiple tees 1104, a green 1106, havinga hole 1108 holding a flagstick 1110 having a flagstick height 1112. Teebox 1102 include a first tee box AI enabled camera (TCAM1) 1114, asecond tee box AI enabled camera (TCAM2) 1116, a third tee box AIenabled camera (TCAM3) 1118. MAIG hole 1100 also includes a tee boxradar unit 1120 positioned near tee box 1102. Green 1106 also includes afirst greenside AI enabled camera (GCAM1) 1122, a second greenside AIenabled camera (GCAM2) 1124, a third greenside AI enabled camera (GCAM3)1126 located around green 1106. Tee box 1102 also includes a teesidemicrophone 1128 and green 1106 also includes a greenside microphone1130. MAIG hole 1100 also includes a second radar unit 1132 positionedaway from tee box 1102 and can include one or more sensor arrays todetect motion on MAIG hole 1100. Tee box 1102 also include a QR golfcode 1146 at one or more of the multiple tees 1104.

MAIG hole 1100 also includes a communication interface 1134 connectingvarious components of MAIG hole 1100 to a remote media system (RMS) 1136having AI golf logic 1148. MAIG hole 1100 further includes a golf coursepower (GCP) source 1138 configured to power various portions of MAIGhole 1100. RMS 1136 is configured to communicate with a network mediaprocessing and management services (NMS) 1140 configured to processvideo recorded and uploaded to NMS 1140. NMS 1140 is configured to be incommunication with one or more destinations 1142 operable to receivedigital media created using MAIG hole 1100 and NMS 1140. Alsoillustrated within FIG. 11 is a mobile device 1144 operable to be usedwith MAIG hole 1100.

According to another aspect, TCAMS 1-3 (1114, 1116, 1118) and GCAMS 1-3(1122, 1124, 1126) can be installed and calibrated from time to time onMAIG hole 1100. For example, each camera can be installed using surveyand GPS data to capture a precise location and overall height of eachinstallation. For example, some cameras may be positioned higher thanothers depending on the topology of MAIG hole 1100. By capturing aprecise location of each of the cameras, the distances between each ofthe cameras can be determined and image data can be used to triangulatelocations of various objects detected within the images or videocaptured by each camera. In some forms, one or more cameras may includeembedded GPS capabilities to assist with locating the coordinates of aninstalled camera on MAIG hole 1100. By having the specific location ofeach of the cameras, distance measurements of objects can be achieved.For example, GCAM 1 1122 and GCAM 3 1126 can be used to triangulatedhole 1108, flagstick 1110, flagstick heights 1112, Tees 1104, golferlocations when playing, distance to hole 1108, distance a ball travelledafter being struck, distance a ball may be to hole 1108 after landing ongreen 1106, or various other distances to areas or objects on MAIG hole1100. Other cameras may also be used. Additionally, various locations onand around green 1106 can be triangulated to create a virtual grid ormap of the area of green 1106. By MAIG hole 1100 being mapped using AIenabled cameras (including different grass cuts, fairway, first cut,rough, fringe, sand, water, etc.) that can be used to identify objectswithin image frames, efficient distance calculations can be created andused during play of MAIG hole 1100.

According to a further aspect, MAIG hole 1100 can include a dailycalibration routine that can be managed by RMS 1134 or NMS 1140. Forexample, depending on the environmental conditions, optical viewperformance may change from time to time which can cause a camera'sfocus to drift slightly. This drift can lead to measurement errors ofdistances of objects within MAIG hole 1100. As such, during an initialset-up, a reference can be provided having a specific height. Areference can be a temporary reference such as a measurement stick orsurveyor's pole. In other forms, the heights of the pole for each of thecameras (not expressly illustrated) can be marked and used as areference for daily calibrations or when image capturing quality maychange. In other forms, the height of a flagstick can be used as areference for determining a specific height to be used to calibrate eachof the cameras.

In other form, each of the cameras can be calibrated based on an opticalor digital zoom level. For example, if GCAM 1 1122 includes an opticalzoom capability of 10×, GCAM 1 1122 can be set to a series of zoomlevels (e.g. 1×, 2×, 5×, 10×, etc.) and calibrated using a referenceobject. In this manner, the overall size of the reference object can bestored within each camera, or RMS 1134 and used to calculate distances.In another form, the number of pixels present at a zoom level of thereference object can be determined and as the zoom level of a camera ischanged, the number of pixels will change for each zoom level and can bestored and used later to determine distances of objects. For example, ata 1× zoom level, the number of pixels captured by the reference objectmay be 1,000 pixels. At a zoom level of 5×, the number of pixels mayincrease to 5,000. Although described as a 1:5 mapping it should beunderstood that the number of pixels may vary based on camera type, lenstype, temperature, errors in lens travel distances during focus, etc.Various other techniques can also be deployed for calibrating GCAMS 1-3(1122, 1124, 1126) and TCAMS 1-3 (1114, 1116, 1118) as needed or desiredto increase optical image capturing and distance accuracy.

According to another aspect, MAIG hole 1100 also includes a tee boxradar unit 1120 and a second radar unit 1132. Each radar unit can becoupled to RMS 1134 for storing radar data detected by each radar unit.In some instances, each radar unit can store data captured andcommunicate the captured data when RMS 1134 requests the data to besent. Radar data can include a time stamped data that can be synced withcaptured video of MAIG hole 1100. According to one form, each of theradars can be used to locate a new daily pin position, and statistics ordata for moving objects such as a golf ball during play. Additionally,radar data can be combined with AI golf logic 1148 to identify golfobjects and location/speed of objects present or located on MAIG hole1100.

According to another aspect, MAIG hole 1100 can record multiple playersshots from multiple points of view or angles. For example, TCAMs 1-3(1114, 1116, 1118) can be used to record an outgoing ball flight for afirst golfer teeing off. Additionally, while the ball is in flight, oneor more green side camera GCAMs 1-3 (1122, 1124, 1126) can record a ballinflight while another of green side cameras can record a ball as itapproaches and lands on green 1106. In this manner, a multi-view videocan be created and multiple-segments for a shot can be presented andcombined into a final video for a user. For example, each video can becreated for a specific golfer, and communicated to NMS 1140 forprocessing. Each video can have a unique session I.D. created duringrecording of video segments for the golfer and NMS 1140 can combine thevideos into a single video of the shot. In other forms, MAIG 1100 canalso be used to create a split screen view for a tee shot by a golfer.For example, if a right-handed golfer is teeing off, the TCAM 1 1114 canrecord from behind tee box 1102 or down the line, while TCAM 2 1112 canbe used to record front view of the golfer's shot. Each of the videoscan be synced up by NMS 1140 and when processed into a final video, bepresented such that the down the line video is presented on one side ofthe final video, and the front view video is presented on the otherside. In this manner, a golfer would receive both views in a singlevideo.

According to another aspect, MAIG hole 1100 can use a single camera totrack the play of multiple golfers playing MAIG hole 1100 together. Forexample, four golfers can approach MAIG hole 1100 as a foursome playinga round of golf together. Each golfer can scan QR golf code 1146 tocreate a session and when it is their turn to take their shot from Teebox 1102. When the first golfer tees off, RMS 1136 using one of TCAMs1-3 (1114, 1116, 1118) and AI logic 1148 will identify the golfer thatscanned QR Golf Code 1146. Upon scanning QR Golf code 1146, image dataof the specific golfer can be captured and saved for subsequent use andprocessing. After each golfer scans QR golf code 1146, a unique sessionI.D. is created and unique aspects of each golfer are detected with RMS1136 and AI logic 1148. After each golfer hits their first shotapproaches their ball, RMS 1136 can assign a camera to record eachgolfers' remaining shots. For example, golfer #1 may have hit a shot tothe back of green 1106. As such, GCAM 1 1122 can be assigned to recordgolfer #1. Additionally, if golfer #2 hit a golf ball to the right ofgreen 1106, GCAM 2 1124 can be assigned to record golfer #2.According toa further aspect, if golfer #3 landed a ball in front of green 1106, atee box cam can be used to record golfer #3. For example, TCAM2 1116 canbe provided as a PTZ camera as described herein and can be rotatedtoward golfer #3 and record the rest of play accordingly. In thismanner, a multiple players can have their shots recorded using a‘personal camera’ and WAIG hole 1100 can record each golfer on a singlevideo session without having to slice an entire video stream intoseparate segments.

According to a further aspect, NMS 1140 can be used with RMS 1136 tocreate a video for each golfer playing in a group. For example, when agolfer scans QR golf code 1146 using their mobile device 1124, a sessioncan be requested by NMS 1140 to allow RMS 1136 to initiate a recordevent for that golfer. The golfer's I.D. and AI detected data can bestored by RMS 1136 and/or NMS 1140 for processing video for thatspecific golfer. Additionally, a camera can also be assigned to thatgolfer based on a detected landing location of a golf ball and storedinto the user's log file for that session. As the next golfer hits, anew session is created for each golfer that scans QR golf code 1146,getting a unique identifier associated with each video created. Uponeach golfer scanning or checking in, WAIG hole 1100 an record eachgolfer and communicate each golfer's video from RMS 1136 to NMS 1140 forpost processing of each video. For example, a log file for each golferidentified can be communicate with each video and can include variousaspects of the shot including radar unit data, videos, golfer names, adistance of hole, a distance of shot, or various other aspects of play.NMS 1140 can then process each of the videos using the unique I.D.generated, and can overlay graphical data to the golfer's name, coursename, hole number and distance, performance data such as number ofstrokes to complete, length of drive or shot, distance to pin, andvarious other forms of hole data. NMS 1140 can also add shot tracing toeach of the tee box shots to further enhance the viewing experience foreach of the golfers. As such, a single video stream can be created by asingle camera assigned to each golfer, and processed by RMS 1136/1140 aseach golfer finishes play on WAIG hole 1100. This will allow forincreased efficiency in production given each golfer finishes a hole atseparate times which will reduce upload times and video processingrequirements creating less of a strain on the overall AIMS supportingWAIG hole 1100.

It will be appreciated that various other additional method steps may beincluded in the above methods, or the above methods may be modified inaccordance with the functionality of the systems and functionalitydescribed above. It will be appreciated that such aspects andembodiments are more than an abstract idea performed by a computer orother controller. The above-described aspects are automaticallyperformed based on a variety of inputs that are not easily accessible ordetermined, and the resulting end product cannot otherwise be providedin the same automatic manner.

Although only a few exemplary embodiments have been described in detailabove, those skilled in the art will readily appreciate that manymodifications are possible in the exemplary embodiments withoutmaterially departing from the novel teachings and advantages of theembodiments of the present disclosure. Accordingly, all suchmodifications are intended to be included within the scope of theembodiments of the present disclosure as defined in the followingclaims. In the claims, means-plus-function clauses are intended to coverthe structures described herein as performing the recited function andnot only structural equivalents, but also equivalent structures.

Note that not all of the activities described above in the generaldescription or the examples are required, that a portion of a specificactivity may not be required, and that one or more further activitiesmay be performed in addition to those described. Still further, theorders in which activities are listed are not necessarily the order inwhich they are performed.

The specification and illustrations of the embodiments described hereinare intended to provide a general understanding of the structure of thevarious embodiments. The specification and illustrations are notintended to serve as an exhaustive and comprehensive description of allof the elements and features of apparatus and systems that use thestructures or methods described herein. Many other embodiments may beapparent to those of skill in the art upon reviewing the disclosure.Other embodiments may be used and derived from the disclosure, such thata structural substitution, logical substitution, or another change maybe made without departing from the scope of the disclosure. Accordingly,the disclosure is to be regarded as illustrative rather thanrestrictive.

Certain features are, for clarity, described herein in the context ofseparate embodiments, may also be provided in combination in a singleembodiment. Conversely, various features that are, for brevity,described in the context of a single embodiment, may also be providedseparately or in any sub combination. Further, reference to valuesstated in ranges includes each and every value within that range.Benefits, other advantages, and solutions to problems have beendescribed above with regard to specific embodiments. However, thebenefits, advantages, solutions to problems, and any feature(s) that maycause any benefit, advantage, or solution to occur or become morepronounced are not to be construed as a critical, required, or essentialfeature of any or all the claims.

The above-disclosed subject matter is to be considered illustrative, andnot restrictive, and the appended claims are intended to cover any andall such modifications, enhancements, and other embodiments that fallwithin the scope of the present invention. Thus, to the maximum extentallowed by law, the scope of the present invention is to be determinedby the broadest permissible interpretation of the following claims andtheir equivalents, and shall not be restricted or limited by theforegoing detailed description.

Although only a few exemplary embodiments have been described in detailabove, those skilled in the art will readily appreciate that manymodifications are possible in the exemplary embodiments withoutmaterially departing from the novel teachings and advantages of theembodiments of the present disclosure. Accordingly, all suchmodifications are intended to be included within the scope of theembodiments of the present disclosure as defined in the followingclaims. In the claims, means-plus-function clauses are intended to coverthe structures described herein as performing the recited function andnot only structural equivalents, but also equivalent structures.

What is claimed is:
 1. A method for autonomously providing digital media comprising: detecting a presence of a golfer at a golf hole on a golf course; receiving an input to initiate a video recording of the golfer using a remote media system (RMS) located near the golf course, the input to initiate the video recording received from a network media processor and service (NMS) communicatively coupled to the RMS and located remote to the RMS without use of a mobile application; automatically recording the golfer present on the golf hole of the golf course using an AI enabled camera positioned near a tee box of the golf hole in response to detecting the golfer near the tee box.
 2. The method of claim 1, further including detecting object movement within a grid of the golf hole and sending radar data to the NMS for additional processing using a radar unit positioned near the golf hole.
 3. The method of claim 1, further comprising detecting the presence in response to motion detected.
 4. The method of claim 1, further comprising detecting the presence in response to a geofence detected.
 5. The method of claim 1, further comprising detecting the presence in response to RFID detection.
 6. The method of claim 1, further comprising deactivating recording in response to a loss of the detected presence.
 7. A system for autonomously providing digital media comprising: a remote media system (RMS) located at a golf course having a golf hole; the RMS including an AI enabled camera positioned near a tee box of the golf hole and configured to automatically record a golfer present on the golf hole, the RMS configured to receive an input to initiate a video recording of the golfer, wherein the input to initiate the video recording is received from a network media processor and service (NMS) communicatively coupled to the RMS and located remote to the RMS; and a radar unit positioned near the golf hole, the radar unit configured to detect object movement within a grid of the golf hole and to send radar data to the NMS for additional processing.
 8. The system of claim 7, wherein the input to initiate the video recording is received without use of a mobile application.
 9. The system of claim 7, further including a mobile application configured to send the input to the NMS to activate the video recording, wherein the input includes a unique identifier of the mobile application, a location of the golf hole, and a user profile identifier of the golfer.
 10. The system of claim 7, further comprising a QR golf code located near the tee box of the golf hole, the QR golf code having a unique graphic identifier encoded on a surface of the QR golf code to identify at least one of the golf course, the golf hole, the AI enabled camera and the tee box.
 11. The system of claim 10, wherein the AI enabled camera is configured to record the golfer present on the golf hole in response to the golfer capturing the QR golf code.
 12. The system of claim 7, wherein the AI enabled camera is in communication with a clubhouse, wherein the clubhouse is configured to display live video or recorded video captured at the AI enabled camera in response to detecting the golfer at the clubhouse.
 13. The system of claim 7, wherein the RMS includes a motion sensor configured to detect motion at the tee box of the golf hole and to initiate activation of the AI enabled camera in response to detecting the motion.
 14. An AI enabled golf course comprising: a first golf hole having a green, a tee box, and a hole with a flagstick positioned within the hole; a remote media system (RMS) located at a golf course having a golf hole; the RMS including an AI enabled camera positioned near a tee box of the golf hole and configured to automatically record a golfer present on the golf hole, the RMS configured to receive an input to initiate a video recording of the golfer, wherein the input to initiate the video recording is received from a network media processor and service (NMS) communicatively coupled to the RMS and located remote to the RMS; and a radar unit positioned near the golf hole, the radar unit configured to detect object movement within a grid of the golf hole and to send radar data to the NMS for additional processing.
 15. The golf course of claim 14, further comprising a power module coupled to the AI enabled camera for providing power to the AI enabled camera.
 16. The golf course of claim 14, further comprising a communication interface configured to receive an input to activate a video recording of the golfer at the golf hole, wherein the video recording includes a plurality of images of the golfer having objects within the images that are detectable using an AI logic.
 17. The golf course of claim 14, further comprising a detection mechanism for detecting when a golfer may be present on the tee box.
 18. The golf course of claim 14, further comprising: a second golf hole having a second green, a second tee box, and a second hole with a flagstick positioned within the second golf hole; and a second AI enabled camera positioned near the second tee box and configured to record a second golfer present on the second golf hole, wherein the recording is in response to detecting the second golfer near the second tee box.
 19. The golf course of claim 14, further comprising a clubhouse, wherein the clubhouse is in communication with the AI enabled camera, wherein the clubhouse is configured to display live video or recorded video captured at the AI enabled camera.
 20. The golf course of claim 19, wherein the clubhouse is configured to display recorded video in response to detecting the golfer at the clubhouse. 